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Yuille, Alan

Bloomberg Distinguished Professor
A&s Cognitive Science

324B Clark Hall
(410) 516-6759
ayuille1@jhu.edu

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About

Education
  • Ph.D. 1976, University of Cambridge
Awards
  • 2015:  Bloomberg Distinguished Professor
  • 2013:  Helmholtz Test of Time Award
  • 2011:  Honorary Degree
  • 2010:  12. Member of the Korean World Class University Program
  • 2009:  IEEE Fellow
  • 2003:  Dean’s Recognition Award
  • 2003:  10. Marr Prize
  • 2000:  Smith-Kettlewell Professor
  • 1993:  Visiting Scientist. Isaac Newton Institute of Mathematics
  • 1992:  Fesler-Lambert Visiting Professor
  • 1988:  Honorary mention Marr Prize
  • 1979:  Rayleigh Research Prize
  • 1979:  N.A.T.O. Research Fellowship
  • 1974:  1. Trinity College Senior Scholarship
  • 1974:  2. Rouse Ball Prizes
Presentations
  • "CGMH Skype Talk", Taiwan CGMH.  Baltimore Maryland, United States of America (the).  December 1, 2018
  • "Early Detection of Pancreatic Cancer: The FELIX project", Lustgarten Foundation Scientific Meeting.  New York, United States of America (the).  November 12, 2018
  • "Deep networks and beyond", Janelia Visit.  Virginia, United States of America (the).  October 19, 2018
  • "Deep networks and beyond", Ian. P. Howard Memorial Lecture at York University.  Ontario, Canada.  October 11, 2018
  • "Deep Networks and Beyond-When Bid Data is not Enough", World Artificial Intelligence Conference.  China.  September 18, 2018
  • "YiTu World Artificial Intelligence Conference".  Beijing, China.  September 18, 2018
  • "World Arti cial Intelligence Conference".  Shanghai, China.  September 18, 2018
  • "AI World Conference".  Beijing, China.  September 18, 2018
  • "Person In Context (PIC) Challenge", ECCV.  Munich, Germany.  September 9, 2018
  • "Learning in Synthetic World", CVPR Workshop.  Munich, Germany.  September 9, 2018
  • "Electronics and Telecommunications Research Institute".  Daejeon, Korea (the Republic of).  July 13, 2018
  • "Korea Advanced Institute of Science and Technology".  Daejeon, Korea (the Republic of).  July 12, 2018
  • "Asan Medical Center".  Seoul, Korea (the Republic of).  July 11, 2018
  • "Korea Unviersity, cognitive science department".  Seoul, Korea (the Republic of).  July 10, 2018
  • "KIST. Seoul".  Seoul, Korea (the Republic of).  July 9, 2018
  • "AI and life", ShanghaiTech: SSIST Conference.  Shanghai, China.  July 2, 2018
  • "Strategic Analysis", Harold Hawkins ONR program review.  Arlington Virginia, United States of America (the).  June 21, 2018
  • "Sol Goldman Think-tank Meeting on Artificial Intelligence as Applied to Pancreatic Cancer".  Baltimore Maryland, United States of America (the).  April 6, 2018
  • "Pancreatic Cancer Collective Innovation Summit, MIT".  Boston Massachusetts, United States of America (the).  April 4, 2018
  • "Board of Trustees Dinner with BDPs".  New York New York, United States of America (the).  March 8, 2018
  • "Academia, Industry, and Society", Academia, Industry, and Society.  Shanghai Jiao Tong, China.  December 1, 2017
  • "David Mumford 80th birthday".  Tsinghua, China.  December 1, 2017
  • "YiTu Technology".  Shanghai, China.  December 1, 2017
  • "Nvidia GTC".  Washington, D.C., United States of America (the).  November 2, 2017
  • "Symmetry", ICCV Workshop.  Venice, Italy.  October 22, 2017
  • "Towards Understandable Deep Networks for Vision", Center for Brains, Minds, and Machines, MIT.  Boston Massachusetts, United States of America (the).  October 13, 2017
  • "Oculus Pittsburgh".  Pittsburgh Pennsylvania, United States of America (the).  October 2, 2017
  • "IDIES Workshop", IDIES Workshop, Physics and Astronomy.  Baltimore Maryland, United States of America (the).  October 1, 2017
  • "CVPR", CVPR Workshop.  Waikiki Beach Hawaii, United States of America (the).  July 21, 2017
  • "Visual Understanding of Humans in Crowd Scene and the 1st Look Into Person (LIP) Challenge", CVPR Workshop.  Waikiki Hawaii, United States of America (the).  July 1, 2017
  • "PASCAL in Detail", CVPR Workshop.  Waikiki Hawaii, United States of America (the).  June 20, 2017
  • "Medical Computer Vision workshop", CVPR Workshop.  Waikiki Hawaii, United States of America (the).  June 20, 2017
  • "Deep Learning Workshop", Deep Learning Workshop.  Maryland, United States of America (the).  May 24, 2017
  • "Talk", BMVC.  London, United Kingdom of Great Britain and Northern Ireland (the).  April 25, 2017
  • "Deep networks and beyond", LCSR Seminar.  Baltimore Maryland, United States of America (the).  April 12, 2017
  • "CBMM AAAI, Stanford", CBMM AAAI.  Palo Alto California, United States of America (the).  March 27, 2017
  • "Physics Colloquium: Neufeld", Physics Department.  Baltimore Maryland, United States of America (the).  February 2, 2017

Publications

Journal Articles
  • Ren Z, Yan J, Yang X, Yuille A, Zha H (2020).  Unsupervised learning of optical flow with patch consistency and occlusion estimation.  Pattern Recognition.  103.
  • Dreizin D, Zhou Y, Chen T, Li G, Yuille AL, McLenithan A, Morrison JJ (2020).  Deep learning-based quantitative visualization and measurement of extraperitoneal hematoma volumes in patients with pelvic fractures: Potential role in personalized forecasting and decision support.  The journal of trauma and acute care surgery.  88(3).  425-433.
  • Weisberg EM, Chu LC, Park S, Yuille AL, Kinzler KW, Vogelstein B, Fishman EK (2020).  Deep lessons learned: Radiology, oncology, pathology, and computer science experts unite around artificial intelligence to strive for earlier pancreatic cancer diagnosis.  Diagnostic and Interventional Imaging.  101(2).  111-115.
  • Dreizin D, Zhou Y, Zhang Y, Tirada N, Yuille AL (2020).  Performance of a Deep Learning Algorithm for Automated Segmentation and Quantification of Traumatic Pelvic Hematomas on CT.  Journal of Digital Imaging.  33(1).  243-251.
  • Xie L, Yu Q, Zhou Y, Wang Y, Fishman EK, Yuille AL (2020).  Recurrent Saliency Transformation Network for Tiny Target Segmentation in Abdominal CT Scans.  IEEE Transactions on Medical Imaging.  39(2).  514-525.
  • Chen H, Fan Z, Lu H, Yuille AL, Rong S (2020).  Preco: A large-scale dataset in preschool vocabulary for coreference resolution.  Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018.  172-181.
  • Park S, Chu LC, Fishman EK, Yuille AL, Vogelstein B, Kinzler KW, Horton KM, Hruban RH, Zinreich ES, Fadaei Fouladi D, Shayesteh S, Graves J, Kawamoto S (2020).  Annotated normal CT data of the abdomen for deep learning: Challenges and strategies for implementation.  Diagnostic and Interventional Imaging.  101(1).  35-44.
  • Tang P, Wang X, Bai S, Shen W, Bai X, Liu W, Yuille A (2020).  PCL: Proposal Cluster Learning for Weakly Supervised Object Detection.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  42(1).  176-191.
  • Liu Q, Xie L, Wang H, Yuille A (2019).  Semantic-aware knowledge preservation for zero-shot sketch-based image retrieval.  Proceedings of the IEEE International Conference on Computer Vision.  2019-October.  3661-3670.
  • Zhou Y, Li Z, Bai S, Chen X, Han M, Wang C, Fishman E, Yuille A (2019).  Prior-aware neural network for partially-supervised multi-organ segmentation.  Proceedings of the IEEE International Conference on Computer Vision.  2019-October.  10671-10680.
  • Gao Y, Yuille AL (2019).  Estimation of 3D Category-Specific Object Structure: Symmetry, Manhattan and/or Multiple Images.  International Journal of Computer Vision.  127(10).  1501-1526.
  • Luo C, Yuille A (2019).  Grouped spatial-temporal aggregation for efficient action recognition.  Proceedings of the IEEE International Conference on Computer Vision.  2019-October.  5511-5520.
  • Liu F, Xia Y, Yang D, Yuille A, Xu D (2019).  An alarm system for segmentation algorithm based on shape model.  Proceedings of the IEEE International Conference on Computer Vision.  2019-October.  10651-10660.
  • Bai Y, Liu Q, Xie L, Zheng Y, Qiu W, Yuille A (2019).  Semantic part detection via matching: Learning to generalize to novel viewpoints from limited training data.  Proceedings of the IEEE International Conference on Computer Vision.  2019-October.  7534-7544.
  • Chu LC, Park S, Kawamoto S, Wang Y, Zhou Y, Shen W, Zhu Z, Xia Y, Xie L, Liu F, Yu Q, Fouladi DF, Shayesteh S, Zinreich E, Graves JS, Horton KM, Yuille AL, Hruban RH, Kinzler KW, Vogelstein B, Fishman EK (2019).  Application of Deep Learning to Pancreatic Cancer Detection: Lessons Learned From Our Initial Experience.  Journal of the American College of Radiology.  16(9).  1338-1342.
  • Mei J, Chen X, Wang C, Yuille A, Lan X, Zeng W (2019).  Learning to Refine 3D Human Pose Sequences.  Proceedings - 2019 International Conference on 3D Vision, 3DV 2019.  358-366.
  • Zhu Z, Liu C, Yang D, Yuille A, Xu D (2019).  V-NAS: Neural Architecture Search for Volumetric Medical Image Segmentation.  Proceedings - 2019 International Conference on 3D Vision, 3DV 2019.  240-248.
  • Wang Y, Zhou Y, Shen W, Park S, Fishman EK, Yuille AL (2019).  Abdominal multi-organ segmentation with organ-attention networks and statistical fusion.  Medical Image Analysis.  55.  88-102.
  • Xie C, Zhang Z, Zhou Y, Bai S, Wang J, Ren Z, Yuille AL (2019).  Improving transferability of adversarial examples with input diversity.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  2019-June.  2725-2734.
  • Xie C, Wu Y, Maaten LVD, Yuille AL, He K (2019).  Feature denoising for improving adversarial robustness.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  2019-June.  501-509.
  • Yang C, Xie L, Su C, Yuille AL (2019).  Snapshot distillation: Teacher-student optimization in one generation.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  2019-June.  2854-2863.
  • Gao Y, Ma J, Zhao M, Liu W, Yuille AL (2019).  NDDR-CNN: Layerwise feature fusing in multi-task cnns by neural discriminative dimensionality reduction.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  2019-June.  3200-3209.
  • Zuo Y, Qiu W, Xie L, Zhong F, Wang Y, Yuille AL (2019).  Craves: Controlling robotic arm with a vision-based economic system.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  2019-June.  4209-4218.
  • Wei C, Xie L, Ren X, Xia Y, Su C, Liu J, Tian Q, Yuille AL (2019).  Iterative reorganization with weak spatial constraints: Solving arbitrary jigsaw puzzles for unsupervised representation learning.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  2019-June.  1910-1919.
  • Liu C, Chen LC, Schroff F, Adam H, Hua W, Yuille AL, Fei-Fei L (2019).  Auto-deeplab: Hierarchical neural architecture search for semantic image segmentation.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  2019-June.  82-92.
  • Liu R, Liu C, Bai Y, Yuille AL (2019).  CLEVR-REF+: Diagnosing visual reasoning with referring expressions.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  2019-June.  4180-4189.
  • Ni T, Xie L, Zheng H, Fishman EK, Yuille AL (2019).  Elastic boundary projection for 3D medical image segmentation.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  2019-June.  2104-2113.
  • Wang H, Kembhavi A, Farhadi A, Yuille AL, Rastegari M (2019).  Elastic: Improving cnns with dynamic scaling policies.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  2019-June.  2253-2262.
  • Zeng X, Liu C, Wang YS, Qiu W, Xie L, Tai YW, Tang CK, Yuille AL (2019).  Adversarial attacks beyond the image space.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  2019-June.  4297-4306.
  • Qiao S, Lin Z, Zhang J, Yuille AL (2019).  Neural rejuvenation: Improving deep network training by enhancing computational resource utilization.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  2019-June.  61-71.
  • Wang C, Wang Y, Lin Z, Yuille AL (2019).  Robust 3D human pose estimation from single images or video sequences.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  41(5).  1227-1241.
  • Zhou Y, Wang Y, Tang P, Bai S, Shen W, Fishman EK, Yuille A (2019).  Semi-supervised 3D abdominal multi-organ segmentation via deep multi-planar co-training.  Proceedings - 2019 IEEE Winter Conference on Applications of Computer Vision, WACV 2019.  121-140.
  • Kim TS, Peven M, Qiu W, Yuille A, Hager GD (2019).  Synthesizing attributes with unreal engine for fine-grained activity analysis.  Proceedings - 2019 IEEE Winter Conference on Applications of Computer Vision Workshops, WACVW 2019.  35-37.
  • Zhou Y, Dreizin D, Li Y, Zhang Z, Wang Y, Yuille A (2019).  Multi-scale Attentional Network for Multi-focal Segmentation of Active Bleed After Pelvic Fractures.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  11861 LNCS.  461-469.
  • Chen Q, Qiu W, Zhang Y, Xie L, Yuille AL (2019).  Sampleahead: Online classifier-sampler communication for learning from synthesized data.  British Machine Vision Conference 2018, BMVC 2018.
  • Mahmood F, Xu W, Durr NJ, Johnson JW, Yuille A (2019).  Structured prediction using cGANs with fusion discriminator.  Deep Generative Models for Highly Structured Data, DGS@ICLR 2019 Workshop.
  • Lin X, Wang H, Li Z, Zhang Y, Yuille A, Lee TS (2019).  Transfer of view-manifold learning to similarity perception of novel objects.  5th International Conference on Learning Representations, ICLR 2017 - Conference Track Proceedings.
  • Chu LC, Park S, Kawamoto S, Fouladi DF, Shayesteh S, Zinreich ES, Graves JS, Horton KM, Hruban RH, Yuille AL, Kinzler KW, Vogelstein B, Fishman EK (2019).  Utility of CT radiomics features in differentiation of pancreatic ductal adenocarcinoma from normal pancreatic tissue.  American Journal of Roentgenology.  213(2).  349-357.
  • Luo C, Chu X, Yuille A (2019).  Orinet: A fully convolutional network for 3D human pose estimation.  British Machine Vision Conference 2018, BMVC 2018.
  • Liu F, Zhou Y, Fishman E, Yuille A (2019).  FusionNet: Incorporating Shape and Texture for Abnormality Detection in 3D Abdominal CT Scans.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  11861 LNCS.  221-229.
  • Zhu Z, Xia Y, Xie L, Fishman EK, Yuille AL (2019).  Multi-scale Coarse-to-Fine Segmentation for Screening Pancreatic Ductal Adenocarcinoma.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  11769 LNCS.  3-12.
  • Luo C, Chu X, Yuille A (2019).  Orinet: A fully convolutional network for 3D human pose estimation.  British Machine Vision Conference 2018, BMVC 2018.
  • Liu F, Xie L, Xia Y, Fishman E, Yuille A (2019).  Joint Shape Representation and Classification for Detecting PDAC.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  11861 LNCS.  212-220.
  • Zhang Z, Zhou Y, Shen W, Fishman E, Yuille A (2019).  Lesion Detection by Efficiently Bridging 3D Context.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  11861 LNCS.  470-478.
  • Zhou Y, Li Y, Zhang Z, Wang Y, Wang A, Fishman EK, Yuille AL, Park S (2019).  Hyper-Pairing Network for Multi-phase Pancreatic Ductal Adenocarcinoma Segmentation.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  11765 LNCS.  155-163.
  • Lin X, Wang H, Li Z, Zhang Y, Yuille A, Lee TS (2019).  Transfer of view-manifold learning to similarity perception of novel objects.  5th International Conference on Learning Representations, ICLR 2017 - Conference Track Proceedings.
  • Qiao S, Liu C, Shen W, Yuille A (2018).  Few-Shot Image Recognition by Predicting Parameters from Activations.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  7229-7238.
  • Yu Q, Xie L, Wang Y, Zhou Y, Fishman EK, Yuille AL (2018).  Recurrent Saliency Transformation Network: Incorporating Multi-stage Visual Cues for Small Organ Segmentation.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  8280-8289.
  • Zhang Z, Qiao S, Xie C, Shen W, Wang B, Yuille AL (2018).  Single-Shot Object Detection with Enriched Semantics.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  5813-5821.
  • Shen W, Guo Y, Wang Y, Zhao K, Wang B, Yuille A (2018).  Deep Regression Forests for Age Estimation.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  2304-2313.
  • Zhang Z, Xie C, Wang J, Xie L, Yuille AL (2018).  DeepVoting: A Robust and Explainable Deep Network for Semantic Part Detection under Partial Occlusion.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  1372-1380.
  • Li Y, Zhang Y, Huang X, Yuille AL (2018).  Deep networks under scene-level supervision for multi-class geospatial object detection from remote sensing images.  ISPRS Journal of Photogrammetry and Remote Sensing.  146.  182-196.
  • Zhang Y, Qiu W, Chen Q, Hu X, Yuille A (2018).  UnrealStereo: Controlling hazardous factors to analyze stereo vision.  Proceedings - 2018 International Conference on 3D Vision, 3DV 2018.  228-237.
  • Zhu Z, Xia Y, Shen W, Fishman E, Yuille A (2018).  A 3D coarse-to-fine framework for volumetric medical image segmentation.  Proceedings - 2018 International Conference on 3D Vision, 3DV 2018.  682-690.
  • Zuo W, Lin L, Yuille AL, Bischof H, Zhang L, Porikli F (2018).  Guest Editorial Introduction to the Special Issue on Large Scale and Nonlinear Similarity Learning for Intelligent Video Analysis.  IEEE Transactions on Circuits and Systems for Video Technology.  28(10).  2441-2448.
  • Cho NG, Yuille A, Lee SW (2018).  A Novel Linelet-Based Representation for Line Segment Detection.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  40(5).  1195-1208.
  • Choi J, Irick KM, Hardin J, Qiu W, Yuille A, Sampson J, Narayanan V (2018).  Stochastic Functional Verification of DNN Design through Progressive Virtual Dataset Generation.  Proceedings - IEEE International Symposium on Circuits and Systems.  2018-May.
  • Cihang Xie, Jianyu Wang, Zhishuai Zhang, Zhou Ren, Yuille AL (2018).  Mitigating adversarial effects through randomization.  ICLR.  1-16.
  • Chen LC, Papandreou G, Kokkinos I, Murphy K, Yuille AL (2018).  DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  40(4).  834-848.
  • Cihang Xie, Jianyu Wang, Zhishuai Zhang, Zhou Ren, Yuille AL (2018).  Mitigating adversarial effects through randomization.  ICLR.  1-16.
  • Alexey Kurakin, Ian Goodfellow, Samy Bengio, Yinpeng Dong, Fangzhou Liao, Ming Liang, Tianyu Pang, Jun Zhu, Xiaolin Hu, Cihang Xie, Jianyu Wang, Zhishuai Zhang, Zhou Ren, Yuille AL, Sangxia Huang, Yao Zhao, Yuzhe Zhao, Zhonglin Han, Junjiajia Long, Yerkebulan Berdibekov, Takuya Akiba, Seiya Tokui, Motoki Abe (2018).  Adversarial Attacks and Defences Competition.  The NIPS 17 Competition Building Intelligent Systems, Springer International Pub.  1-36.
  • Dong X, Bonev BI, Li W, Qiu W, Chen X, Yuille AL (2018).  Ground-Truth Data Set and Baseline Evaluations for Base-Detail Separation Algorithms at the Part Level.  IEEE Transactions on Circuits and Systems for Video Technology.  28(3).  802-806.
  • Wang F, Xiang X, Liu C, Tran TD, Reiter A, Hager GD, Quon H, Cheng J, Yuille AL (2018).  Regularizing face verification nets for pain intensity regression.  Proceedings - International Conference on Image Processing, ICIP.  2017-September.  1087-1091.
  • Jianyu Wang, Zhishuai Zhang, Cihang Xie, Yuyin Zhou, Vittal Premachandran, Jun Zhu, Lingxi Xie, Yuille AL (2018).  Visual Concepts and Compositional Voting.  Annals of Mathematical Sciences and Applications.  3(1, 151–188, 2018).  1-38.
  • Chenxu Luo, Xiao Chu, Yuille AL (2018).  OriNet: A Fully Convolutional Network for 3D Human Pose Estimation.  BMVC.  1-14.
  • Zhishuai Zhang, Siyuan Qiao, Cihang Xie, Wei Shen, Bo Wang, Yuille AL (2018).  Single-Shot Object Detection with Enriched Semantics.  CVPR.  1-9.
  • Jinhang Choi, Kevin M Irick, Justin Hardin, Weichao Qiu, Yuille AL, Jack Sampson, Vijaykrishnan Narayanan (2018).  Stochastic Functional Verification of DNN Design through Progressive Virtual Dataset Generation.  ISCAS.  1-5.
  • Yu-Siang Wang, Chenxi Liu, Xiaohui Zeng, Yuille AL (2018).  Scene Graph Parsing as Dependency Parsing.  ISCAS.  1-11.
  • Zhishuai Zhang, Cihang Xie, Jianyu Wang, Lingxi Xie, Yuille AL (2018).  DeepVoting: An Explainable Framework for Semantic Part Detection under Partial Occlusion.  CVPR.  1-9.
  • Tang P, Wang X, Wang A, Yan Y, Liu W, Huang J, Yuille A (2018).  Weakly Supervised Region Proposal Network and Object Detection.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  11215 LNCS.  370-386.
  • Peng Tang, Xinggang Wang, Angtian Wang, Yongluan Yan, Wenyu Liu, Junzhou Huang, Yuille AL (2018).  Weakly Supervised Region Proposal Network and Object Detection.  ECCV.  1-17.
  • Siyuan Qiao, Wei Shen, Zhishuai Zhang, Bo Wang, Yuille AL (2018).  Deep Co-Training for Semi-Supervised Image Recognition.  ECCV.  1-18.
  • Siyuan Qiao, Zhishuai Zhang, Wei Shen, Bo Wang, Yuille AL (2018).  Gradually Updated Neural Networks for Large-Scale Image Recognition.  ICML.  1-10.
  • Chunyu Wang, Yizhou Wang, Zhouchen Lin, Yuille AL (2018).  Robust 3D Human Pose Estimation from Single Images or Video Sequences.  PAMI.  6(1).  1-14.
  • Qi Chen, Weichao Qiu, Yi Zhang, Lingxi Xie, Yuille AL (2018).  SampleAhead: Online Classifier-Sampler Communication for Learning from Synthesized Data.  BMVC.  1-12.
  • Zhuotun Zhu, Yingda Xia, Wei Shen, Elliot K Fishman, Yuille AL (2018).  A 3D Coarse-to-Fine Framework for Volumetric Medical Image Segmentation.  3DV.  1-9.
  • Chenxi Liu, Barret Zoph, Maxim Neumann, Jonathon Shlens, Wei Hua, Li-Jia Li, Li Fei-Fei, Yuille AL, Jonathan Huang, Kevin Murphy (2018).  Progressive Neural Architecture Search.  ECCV.  1-16.
  • Peng Tang, Xinggang Wang, Song Bai, Wei Shen, Xiang Bai, Wenyu Liu, Yuille AL (2018).  PCL: Proposal Cluster Learning for Weakly Supervised Object Detection.  PAMI.  1-16.
  • Yi Zhang, Weichao Qiu, Qi Chen, Xiaolin Hu, Yuille AL (2018).  UnrealStereo: Controlling Hazardous Factors to Analyze Stereo Vision.  3DV.  1-10.
  • Qiao S, Zhang Z, Shen W, Wang B, Yuille A (2018).  Gradually updated neural networks for large-scale image recognition.  35th International Conference on Machine Learning, ICML 2018.  9.  6676-6686.
  • Wei Shen, Yilu Guo, Yan Wang, Kai Zhao, Bo Wang, Yuille AL (2018).  Deep Regression Forests for Age Estimation.  CVPR.  1-10.
  • Wang Y, Xie L, Qiao S, Zhang Y, Zhang W, Yuille AL (2018).  Multi-scale Spatially-Asymmetric Recalibration for Image Classification.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  11217 LNCS.  523-539.
  • Qihang Yu, Lingxi Xie, Yan Wang, Yuyin Zhou, Elliot K. Fishman, Yuille AL (2018).  Recurrent Saliency Transformation Network:Incorporating Multi-Stage Visual Cues for Small Organ Segmentation.  CVPR.  1-10.
  • Jiang W, Long M, Yang LT, Liu X, Jin H, Yuille AL, Chi Y (2018).  FIPIP: A novel fine-grained parallel partition based intra-frame prediction on heterogeneous many-core systems.  Future Generation Computer Systems.  78.  316-329.
  • Hong Chen, Zhenhua Fan, Hao Lu, Alan Yuille, Shu Rong, Yuille AL (2018).  PreCo: A Large-scale Dataset in Preschool Vocabulary for Coreference Resolution.  EMNLP.  172-181.
  • Xia Y, Xie L, Liu F, Zhu Z, Fishman EK, Yuille AL (2018).  Bridging the Gap Between 2D and 3D Organ Segmentation with Volumetric Fusion Net.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  11073 LNCS.  445-453.
  • Yingda Xia, Lingxi Xie, Fengze Liu, Zhuotun Zhu, Elliot K. Fishman, Yuille AL (2018).  Bridging the Gap Between 2D and 3D Organ Segmentation with Volumetric Fusion Net.  MICCAI.  1-9.
  • Xie C, Zhang Z, Yuille AL, Wang J, Ren Z (2018).  Mitigating adversarial effects through randomization.  6th International Conference on Learning Representations, ICLR 2018 - Conference Track Proceedings.
  • Siyuan Qiao, Chenxi Liu, Wei Shen, Yuille AL (2018).  Few-Shot Image Recognition by Predicting Parameters from Activations.  CVPR.  1-10.
  • Liu C, Zoph B, Neumann M, Shlens J, Hua W, Li LJ, Fei-Fei L, Yuille A, Huang J, Murphy K (2018).  Progressive Neural Architecture Search.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  11205 LNCS.  19-35.
  • Qiao S, Shen W, Zhang Z, Wang B, Yuille A (2018).  Deep co-training for semi-supervised image recognition.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  11219 LNCS.  142-159.
  • Wang Y, Zhou Y, Tang P, Shen W, Fishman EK, Yuille AL (2018).  Training Multi-organ Segmentation Networks with Sample Selection by Relaxed Upper Confident Bound.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  11073 LNCS.  434-442.
  • Yan Wang, Lingxi Xie, Siyuan Qiao, Ya Zhang, Wenjun Zhang, Yuille AL (2018).  Multi-Scale Spatially-Asymmetric Recalibration for Image Classification.  ECCV.  1-17.
  • Yan Wang, Yuyin Zhou, Peng Tang, Wei Shen, Elliot K. Fishman, Yuille AL (2018).  Training Multi-organ Segmentation Networks with Sample Selection by Relaxed Upper Confident Bound.  MICCAI.  1-9.
  • Shen W, Wang B, Jiang Y, Wang Y, Yuille A (2017).  Multi-stage Multi-recursive-input Fully Convolutional Networks for Neuronal Boundary Detection.  Proceedings of the IEEE International Conference on Computer Vision.  2017-October.  2410-2419.
  • Wang Y, Xie L, Liu C, Qiao S, Zhang Y, Zhang W, Tian Q, Yuille A (2017).  SORT: Second-Order Response Transform for Visual Recognition.  Proceedings of the IEEE International Conference on Computer Vision.  2017-October.  1368-1377.
  • Xie L, Yuille A (2017).  Genetic CNN.  Proceedings of the IEEE International Conference on Computer Vision.  2017-October.  1388-1397.
  • Liu C, Lin Z, Shen X, Yang J, Lu X, Yuille A (2017).  Recurrent Multimodal Interaction for Referring Image Segmentation.  Proceedings of the IEEE International Conference on Computer Vision.  2017-October.  1280-1289.
  • Xie C, Wang J, Zhang Z, Zhou Y, Xie L, Yuille A (2017).  Adversarial Examples for Semantic Segmentation and Object Detection.  Proceedings of the IEEE International Conference on Computer Vision.  2017-October.  1378-1387.
  • Qiao S, Shen W, Qiu W, Liu C, Yuille A (2017).  ScaleNet: Guiding Object Proposal Generation in Supermarkets and beyond.  Proceedings of the IEEE International Conference on Computer Vision.  2017-October.  1809-1818.
  • Chu X, Yang W, Ouyang W, Ma C, Yuille AL, Wang X (2017).  Multi-context attention for human pose estimation.  Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017.  2017-January.  5669-5678.
  • Xia F, Wang P, Chen X, Yuille A (2017).  Joint multi-person pose estimation and semantic part segmentation.  Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017.  2017-January.  6080-6089.
  • Gao Y, Yuille AL (2017).  Exploiting symmetry and/or manhattan properties for 3D object structure estimation from single and multiple images.  Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017.  2017-January.  6718-6727.
  • Shen W, Zhao K, Jiang Y, Wang Y, Bai X, Yuille A (2017).  DeepSkeleton: Learning Multi-Task Scale-Associated Deep Side Outputs for Object Skeleton Extraction in Natural Images.  IEEE Transactions on Image Processing.  26(11).  5298-5311.
  • Girshick R, Kokkinos I, Laptev I, Malik J, Papandreou G, Vedaldi A, Wang X, Yan S, Yuille A (2017).  Editorial- Deep Learning for Computer Vision.  Computer Vision and Image Understanding.  164.  1-2.
  • Wang F, Xiang X, Cheng J, Yuille AL (2017).  NormFace: L2 hypersphere embedding for face verification.  MM 2017 - Proceedings of the 2017 ACM Multimedia Conference.  1041-1049.
  • Qiu W, Zhong F, Zhang Y, Qiao S, Xiao Z, Kim TS, Wang Y, Yuille A (2017).  UnrealCV: Virtual worlds for computer vision.  MM 2017 - Proceedings of the 2017 ACM Multimedia Conference.  1221-1224.
  • Jahangiri E, Yuille AL (2017).  Generating Multiple Diverse Hypotheses for Human 3D Pose Consistent with 2D Joint Detections.  Proceedings - 2017 IEEE International Conference on Computer Vision Workshops, ICCVW 2017.  2018-January.  805-814.
  • Premachandran V, Bonev B, Lian X, Yuille A (2017).  PASCAL boundaries: A semantic boundary dataset with a deep semantic boundary detector.  Proceedings - 2017 IEEE Winter Conference on Applications of Computer Vision, WACV 2017.  73-81.
  • Gao Y, Ma J, Yuille AL (2017).  Semi-Supervised Sparse Representation Based Classification for Face Recognition with Insufficient Labeled Samples.  IEEE Transactions on Image Processing.  26(5).  2545-2560.
  • Fangting Xia, Peng Wang, Xianjie Chen, Yuille AL (2017).  Joint Multi-Person Pose Estimation and Semantic Part Segmentation.  CVPR.  1-10.
  • Yan Wang, Lingxi Xie, Chenxi Liu, Siyuan Qiao, Ya Zhang, Wenjun Zhang, Qi Tian, Yuille AL (2017).  SORT: Second-Order Response Transform for Visual Recognition.  ICCV.  1-10.
  • Chang Liu, Fuchun Sun, Changhu Wang, Feng Wang, Yuille AL (2017).  MAT: A Multimodal Attentive Translator for Image Captioning.  IJCAI.  1-7.
  • Alex Wong, Brian Taylor, Yuille AL (2017).  Exploiting Protrusion Cues for Fast and Effective Shape Matching via Ellipses.  BMVC.  1-13.
  • Wei Shen, Kai Zhao, Yilu Guo, Yuille AL (2017).  Label Distribution Learning Forests.  NIPS.  1-10.
  • Ross Girshick, Iasonas Kokkinos, Ivan Laptev, Jitendra Malik, George Papandreou, Andrea Vedaldi, Xiaogang Wang, Shuicheng Yan, Yuille AL (2017).  Deep Learning for Computer Vision.  Computer Vision and Image Understanding.  1-2.
  • Zhuotun Zhu, Lingxi Xie, Yuille AL (2017).  Object Recognition with and without Objects.  IJCAI.  1-7.
  • Zhou Ren, Hailin Jin, Zhe Lin, Chen Fang, Yuille AL (2017).  Multiple Instance Visual-Semantic Embedding.  BMVC.  1-12.
  • Jianyu Wang, Cihang Xie, Zhishuai Zhang, Jun Zhu, Lingxi Xie, Yuille AL (2017).  Detecting Semantic Parts on Partially Occluded Objects.  BMVC.  1-13.
  • Xingyu Lin, Hao Wang, Zhihao Li, Yimeng Zhang, Yuille AL, Tai Sing Lee (2017).  Transfer of View-manifold Learning to Similarity Perception of Novel Objects.  ICLR.  1-13.
  • Yuyin Zhou, Lingxi Xie, Wei Shen, Yan Wang, Elliot Fishman, Yuille AL (2017).  A Fixed-Point Model for Pancreas Segmentation in Abdominal CT Scans.  MICCAI.  1-8.
  • Cheng Ma, Wanli Ouyang, Wei Yang, Xiao Chu, Yuille AL (2017).  Multi-Context Attention for Human Pose Estimation.  CVPR.  1-10.
  • Vittal Premachandran, Boyan Bonev, Xiaochen Lian, Yuille AL (2017).  PASCAL Boundaries: A Semantic Boundary Dataset with A Deep Semantic Boundary Detector.  WACV.  1-9.
  • Wei Shen, Bin Wang, Yuan Jiang, Yan Wang, Yuille AL (2017).  Multi-stage Multi-recursive-input Fully Convolutional Networks for Neuronal Boundary Detection.  ICCV.  1-10.
  • Siyuan Qiao, Wei Shen, Weichao Qiu, Chenxi Liu, Yuille AL (2017).  ScaleNet: Guiding Object Proposal Generation in Supermarkets and Beyond.  ICCV.  1-10.
  • Chenxi Liu, Zhe Lin, Xiaohui Shen, Jimei Yang, Xin Lu, Yuille AL (2017).  Recurrent Multimodal Interaction for Referring Image Segmentation.  ICCV.  1-10.
  • Ehsan Jahangiri, Yuille AL (2017).  Generating Multiple Diverse Hypotheses for Human 3D Pose Consistent with 2D Joint Detections.  ICCV.  1-10.
  • Yuyin Zhou, Lingxi Xie, Elliot Fishman, Yuille AL (2017).  Deep Supervision for Pancreatic Cyst Segmentation in Abdominal CT Scans.  MICCAI.  1-8.
  • Yuan Gao, Yuille AL (2017).  Exploiting Symmetry and/or Manhattan Properties for 3D Object Structure Estimation from Single and Multiple Images.  CVPR.  1-10.
  • Xiao Chu, Wei Yang, Wanli Ouyang, Cheng Ma, Yuille AL (2017).  Multi-Context Attention for Human Pose Estimation.  CVPR.  1-10.
  • Lingxi Xie, Yuille AL (2017).  Genetic CNN.  ICCV.  1-13.
  • Xingyu Lin, Hao Wang, Zhihao Li, Yimeng Zhang, Yuille AL, Tai Sing Lee (2017).  ransfer of View-manifold Learning to Similarity Perception of Novel Objects.  ICLR.  1-13.
  • Yuille AL, Vittal Premachandran, Boyan Bonev, Xiaochen Lian (2017).  PASCAL Boundaries: A Semantic Boundary Dataset with A Deep Semantic Boundary Detector.  WACV.  1-9.
  • Chenxi Liu, Junhua Mao, Fei Sha, Yuille AL (2017).  Attention Correctness in Neural Image Captioning.  AAAI.  1-7.
  • Feng Wang, Xiang Xiang, Jian Cheng, Yuille AL (2017).  NormFace: L2 Hypersphere Embedding for Face Verification.  ACM Multimedia.  1-11.
  • Carolina Lugo-Fagundo, Bert Vogelstein, Yuille AL, Elliot K Fishman (2017).  Deep Learning in Radiology: Now the Real Work Begins.  Journal of the American College of Radiology.  1-4.
  • Liang-Chieh Chen, George Papandreou, Iasonas Kokkinos, Kevin Murphy, Yuille AL (2017).  DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs.  PAMI.  1-14.
  • Cihang Xie, Jianyu Wang, Zhishuai Zhang, Yuyin Zhou, Lingxi Xie, Yuille AL (2017).  Adversarial Examples for Semantic Segmentation and Object Detection.  ICCV.  1-13.
  • Wong A, Taylor B, Yuille A (2017).  Exploiting protrusion cues for fast and effective shape modeling via ellipses.  British Machine Vision Conference 2017, BMVC 2017.
  • Zhu Z, Xie L, Yuille A (2017).  Object recognition with and without objects.  IJCAI International Joint Conference on Artificial Intelligence.  3609-3615.
  • Liu C, Sun F, Wang C, Wang F, Yuille A (2017).  MAT: A multimodal attentive translator for image captioning.  IJCAI International Joint Conference on Artificial Intelligence.  4033-4039.
  • Wang J, Xie C, Zhang Z, Zhu J, Xie L, Yuille AL (2017).  Detecting semantic parts on partially occluded objects.  British Machine Vision Conference 2017, BMVC 2017.
  • Zhou Y, Xie L, Fishman EK, Yuille AL (2017).  Deep supervision for pancreatic cyst segmentation in abdominal CT scans.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  10435 LNCS.  222-230.
  • Ren Z, Jin H, Lin Z, Fang C, Yuille A (2017).  Multiple instance visual-semantic embedding.  British Machine Vision Conference 2017, BMVC 2017.
  • Liu C, Mao J, Sha F, Yuille A (2017).  Attention correctness in neural image captioning.  31st AAAI Conference on Artificial Intelligence, AAAI 2017.  4176-4182.
  • Wong A, Taylor B, Yuille A (2017).  Exploiting protrusion cues for fast and effective shape modeling via ellipses.  British Machine Vision Conference 2017, BMVC 2017.
  • Shen W, Zhao K, Guo Y, Yuille A (2017).  Label distribution learning forests.  Advances in Neural Information Processing Systems.  2017-December.  835-844.
  • Premachandran V, Tarlow D, Yuille AL, Batra D (2017).  Empirical Minimum Bayes Risk Prediction.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  39(1).  75-86.
  • Zhou Y, Xie L, Shen W, Wang Y, Fishman EK, Yuille AL (2017).  A fixed-point model for pancreas segmentation in abdominal CT scans.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  10433 LNCS.  693-701.
  • Chen LC, Barron JT, Papandreou G, Murphy K, Yuille AL (2016).  Semantic image segmentation with task-specific edge detection using CNNs and a discriminatively trained domain transform.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  2016-December.  4545-4554.
  • Chen LC, Yang Y, Wang J, Xu W, Yuille AL (2016).  Attention to Scale: Scale-Aware Semantic Image Segmentation.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  2016-December.  3640-3649.
  • Wang C, Wang Y, Yuille AL (2016).  Mining 3D Key-Pose-Motifs for Action Recognition.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  2016-December.  2639-2647.
  • Xie L, Zheng L, Wang J, Yuille A, Tian Q (2016).  InterActive: Inter-Layer Activeness Propagation.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  2016-December.  270-279.
  • Mao J, Huang J, Toshev A, Camburu O, Yuille A, Murphy K (2016).  Generation and comprehension of unambiguous object descriptions.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  2016-December.  11-20.
  • Ren Z, Jin H, Lin Z, Fang C, Yuille A (2016).  Joint image-text representation by Gaussian Visual-Semantic Embedding.  MM 2016 - Proceedings of the 2016 ACM Multimedia Conference.  207-211.
  • Yuille A, Mottaghi R (2016).  Complexity of representation and inference in compositional models with part sharing.  Journal of Machine Learning Research.  17.
  • Lu H, Rojas RR, Beckers T, Yuille AL (2016).  A Bayesian Theory of Sequential Causal Learning and Abstract Transfer.  Cognitive Science.  40(2).  404-439.
  • Gao Y, Yuille AL (2016).  Symmetric non-rigid structure from motion for category-specific object structure estimation.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  9906 LNCS.  408-424.
  • Wang P, Shen X, Russell B, Cohen S, Price B, Yuille A (2016).  SURGE: Surface regularized geometry estimation from a single image.  Advances in Neural Information Processing Systems.  172-180.
  • Ma J, Zhao J, Yuille AL (2016).  Non-rigid point set registration by preserving global and local structures.  IEEE Transactions on Image Processing.  25(1).  53-64.
  • Qiu W, Yuille A (2016).  UnrealCV: Connecting computer vision to unreal engine.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  9915 LNCS.  909-916.
  • Mao J, Xu J, Jing Y, Yuille A (2016).  Training and evaluating multimodal word embeddings with large-scale web annotated images.  Advances in Neural Information Processing Systems.  442-450.
  • Jiang W, Luol B, Jin H, Yuille AL, Xiao J (2016).  A novel parallelized feature extraction in grouped scale space based on graphic processing units.  Journal of Internet Technology.  17(5).  1061-1069.
  • Mottaghi R, Fidler S, Yuille A, Urtasun R, Parikh D (2016).  Human-Machine CRFs for Identifying Bottlenecks in Scene Understanding.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  38(1).  74-87.
  • Wang P, Yuille A (2016).  Doc: Deep occlusion estimation from a single image.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  9905 LNCS.  545-561.
  • Wang C, Flynn J, Wang Y, Yuille AL (2016).  Recognizing actions in 3D using action-snippets and activated simplices.  30th AAAI Conference on Artificial Intelligence, AAAI 2016.  3604-3610.
  • Xia F, Wang P, Chen LC, Yuille AL (2016).  Zoom better to see clearer: Human and object parsing with hierarchical auto-zoom net.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  9909 LNCS.  648-663.
  • Xia F, Zhu J, Wang P, Yuille AL (2016).  Pose-guided human parsing by an AND/OR graph using pose-context features.  30th AAAI Conference on Artificial Intelligence, AAAI 2016.  3632-3640.
  • Xie L, Tian Q, Flynn J, Wang J, Yuille A (2016).  Geometric neural phrase pooling: Modeling the spatial Co-occurrence of neurons.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  9905 LNCS.  645-661.
  • Wang P, Shen X, Lin Z, Cohen S, Price B, Yuille A (2015).  Towards unified depth and semantic prediction from a single image.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  07-12-June-2015.  2800-2809.
  • Wang J, Yuille A (2015).  Semantic part segmentation using compositional model combining shape and appearance.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  07-12-June-2015.  1788-1797.
  • Dong X, Bonev B, Zhu Y, Yuille AL (2015).  Region-based temporally consistent video post-processing.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  07-12-June-2015.  714-722.
  • Zhu Y, Zhang Y, Bonev B, Yuille AL (2015).  Modeling deformable gradient compositions for single-image super-resolution.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  07-12-June-2015.  5417-5425.
  • Chen X, Yuille A (2015).  Parsing occluded people by flexible compositions.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  07-12-June-2015.  3945-3954.
  • Ma J, Qiu W, Zhao J, Ma Y, Yuille AL, Tu Z (2015).  Robust L2E estimation of transformation for non-rigid registration.  IEEE Transactions on Signal Processing.  63(5).  1115-1129.
  • Wong A, Yuille A (2015).  One shot learning via compositions of meaningful patches.  Proceedings of the IEEE International Conference on Computer Vision.  2015 International Conference on Computer Vision, ICCV 2015.  1197-1205.
  • Ren Z, Wang C, Yuille A (2015).  Scene-domain active part models for object representation.  Proceedings of the IEEE International Conference on Computer Vision.  2015 International Conference on Computer Vision, ICCV 2015.  2497-2505.
  • Wang P, Shen X, Lin Z, Cohen S, Price B, Yuille A (2015).  Joint object and part segmentation using deep learned potentials.  Proceedings of the IEEE International Conference on Computer Vision.  2015 International Conference on Computer Vision, ICCV 2015.  1573-1581.
  • Papandreou G, Chen LC, Murphy KP, Yuille AL (2015).  Weakly-and semi-supervised learning of a deep convolutional network for semantic image segmentation.  Proceedings of the IEEE International Conference on Computer Vision.  2015 International Conference on Computer Vision, ICCV 2015.  1742-1750.
  • Mao J, Wei X, Yang Y, Wang J, Huang Z, Yuille AL (2015).  Learning like a child: Fast novel visual concept learning from sentence descriptions of images.  Proceedings of the IEEE International Conference on Computer Vision.  2015 International Conference on Computer Vision, ICCV 2015.  2533-2541.
  • Mao J, Xu W, Yang Y, Wang J, Huang Z, Yuille A (2015).  Deep captioning with multimodal recurrent neural networks (m-RNN).  3rd International Conference on Learning Representations, ICLR 2015 - Conference Track Proceedings.
  • Chen LC, Schwing AG, Yuille AL, Urtasun R (2015).  Learning deep structured models.  32nd International Conference on Machine Learning, ICML 2015.  3.  1785-1794.
  • Chen LC, Schwing AG, Yuille AL, Urtasun R (2015).  Learning deep structured models.  3rd International Conference on Learning Representations, ICLR 2015 - Workshop Track Proceedings.
  • Wang P, Yuille A (2015).  Error factor analysis for wild scene image-labelling.  Proceedings - 2015 IEEE Winter Conference on Applications of Computer Vision, WACV 2015.  781-788.
  • Chen LC, Papandreou G, Kokkinos I, Murphy K, Yuille AL (2015).  Semantic image segmentation with deep convolutional nets and fully connected CRFs.  3rd International Conference on Learning Representations, ICLR 2015 - Conference Track Proceedings.
  • Dong X, Yuan L, Li W, Yuille AL (2015).  Temporally consistent region-based video exposure correction.  Proceedings - IEEE International Conference on Multimedia and Expo.  2015-August.
  • Anderson A, Douglas PK, Kerr WT, Haynes VS, Yuille AL, Xie J, Wu YN, Brown JA, Cohen MS (2014).  Non-negative matrix factorization of multimodal MRI, fMRI and phenotypic data reveals differential changes in default mode subnetworks in ADHD.  NeuroImage.  102(P1).  207-219.
  • Ma J, Zhao J, Tian J, Yuille AL, Tu Z (2014).  Robust point matching via vector field consensus.  IEEE Transactions on Image Processing.  23(4).  1706-1721.
  • Zhu J, Mao J, Yuille A (2014).  Learning from weakly supervised data by the expectation loss SVM (e-SVM) algorithm.  Advances in Neural Information Processing Systems.  2(January).  1125-1133.
  • Guo G, Wang Y, Jiang T, Yuille AL, Fang F, Gao W (2014).  A shape reconstructability measure of object part importance with applications to object detection and localization.  International Journal of Computer Vision.  108(3).  241-258.
  • Lu W, Lian X, Yuille A (2014).  Parsing semantic parts of cars using graphical models and segment appearance consistency.  BMVC 2014 - Proceedings of the British Machine Vision Conference 2014.
  • Qiu W, Wang X, Bai X, Yuille A, Tu Z (2014).  Scale-space SIFT flow.  2014 IEEE Winter Conference on Applications of Computer Vision, WACV 2014.  1112-1119.
  • Chen LC, Fidler S, Yuille AL, Urtasun R (2014).  Beat the MTurkers: Automatic image labeling from weak 3D supervision.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  3198-3205.
  • Wang C, Wang Y, Lin Z, Yuille AL, Gao W (2014).  Robust estimation of 3D human poses from a single image.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  2369-2376.
  • Mottaghi R, Chen X, Liu X, Cho NG, Lee SW, Fidler S, Urtasun R, Yuille A (2014).  The role of context for object detection and semantic segmentation in the wild.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  891-898.
  • Dong J, Chen Q, Yan S, Yuille A (2014).  Towards unified object detection and semantic segmentation.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  8693 LNCS(PART 5).  299-314.
  • Zhu Y, Zhang Y, Yuille AL (2014).  Single image super-resolution using deformable patches.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  2917-2924.
  • Li Y, Hou X, Koch C, Rehg JM, Yuille AL (2014).  The secrets of salient object segmentation.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  280-287.
  • Chen X, Mottaghi R, Liu X, Fidler S, Urtasun R, Yuille A (2014).  Detect what you can: Detecting and representing objects using holistic models and body parts.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  1979-1986.
  • Mao J, Zhu J, Yuille AL (2014).  An active patch model for real world texture and appearance classification.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  8691 LNCS(PART 3).  140-155.
  • Yuille AL, Luo J (2014).  Guest editorial: Geometry, lighting, motion, and learning.  International Journal of Computer Vision.  107(2).  99-100.
  • Chen X, Yuille A (2014).  Articulated pose estimation by a graphical model with image dependent pairwise relations.  Advances in Neural Information Processing Systems.  2(January).  1736-1744.
  • Bonev B, Yuille AL (2014).  A fast and simple algorithm for producing candidate regions.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  8691 LNCS(PART 3).  535-549.
  • Papandreou G, Chen LC, Yuille AL (2014).  Modeling image patches with a generic dictionary of mini-epitomes.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  2059-2066.
  • Hou X, Yuille A, Koch C (2013).  Boundary detection benchmarking: Beyond F-measures.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  2123-2130.
  • Wang C, Wang Y, Yuille AL (2013).  An approach to pose-based action recognition.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  915-922.
  • Ma J, Zhao J, Tian J, Tu Z, Yuille AL (2013).  Robust estimation of nonrigid transformation for point set registration.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  2147-2154.
  • Fidler S, Mottaghi R, Yuille A, Urtasun R (2013).  Bottom-up segmentation for top-down detection.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  3294-3301.
  • Liu X, Lin L, Yuille AL (2013).  Robust region grouping via internal patch statistics.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  1931-1938.
  • Cho NG, Yuille AL, Lee SW (2013).  Adaptive occlusion state estimation for human pose tracking under self-occlusions.  Pattern Recognition.  46(3).  649-661.
  • Chen LC, Papandreou G, Yuille AL (2013).  Learning a dictionary of shape epitomes with applications to image labeling.  Proceedings of the IEEE International Conference on Computer Vision.  337-344.
  • Yuille AL, Mottaghi R (2013).  Complexity of representation and inference in compositional models with part sharing.  1st International Conference on Learning Representations, ICLR 2013 - Conference Track Proceedings.
  • Cho NG, Yuille A, Lee SW (2012).  Self-occlusion robust 3D human pose tracking from monocular image sequence.  Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics.  254-257.
  • Yuille A, He X (2012).  Probabilistic models of vision and max-margin methods.  Frontiers of Electrical and Electronic Engineering in China.  7(1).  94-106.
  • Yuille AL (2012).  Computer vision needs a core and foundations.  Image and Vision Computing.  30(8).  469-471.
  • Zhu L, Chen Y, Lin Y, Lin C, Yuille A (2012).  Recursive segmentation and recognition templates for image parsing.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  34(2).  359-371.
  • Nishiyama Y, Ye X, Yuille AL (2012).  A family of CCCP algorithms which minimize the TRW free energy.  New Generation Computing.  30(1).  3-16.
  • Lee JJ, Lee PH, Lee SW, Yuille A, Koch C (2011).  AdaBoost for text detection in natural scene.  Proceedings of the International Conference on Document Analysis and Recognition, ICDAR.  429-434.
  • Papandreou G, Yuille AL (2011).  Efficient variational inference in large-scale Bayesian compressed sensing.  Proceedings of the IEEE International Conference on Computer Vision.  1332-1339.
  • Guo G, Wang Y, Jiang T, Yuille A, Gao W (2011).  Computing importance of 2D contour parts by reconstructability.  Proceedings of the IEEE International Conference on Computer Vision.  1364-1371.
  • Mottaghi R, Ranganathan A, Yuille A (2011).  A compositional approach to learning part-based models of objects.  Proceedings of the IEEE International Conference on Computer Vision.  561-568.
  • Cho NG, Yuille A, Lee SW (2011).  Nonflat observation model and adaptive depth order estimation for 3D human pose tracking.  1st Asian Conference on Pattern Recognition, ACPR 2011.  382-386.
  • Papandreou G, Yuille AL (2011).  Perturb-and-MAP random fields: Using discrete optimization to learn and sample from energy models.  Proceedings of the IEEE International Conference on Computer Vision.  193-200.
  • Yuille AL (2011).  Towards a theory of compositional learning and encoding of objects.  Proceedings of the IEEE International Conference on Computer Vision.  1448-1455.
  • Ye X, Yuille A (2011).  Learning a dictionary of deformable patches using GPUs.  Proceedings of the IEEE International Conference on Computer Vision.  483-490.
  • Zhu L, Chen Y, Yuille A (2011).  Recursive compositional models for vision: Description and review of recent work.  Journal of Mathematical Imaging and Vision.  41(1-2).  122-146.
  • Kokkinos I, Yuille A (2011).  Inference and learning with hierarchical shape models.  International Journal of Computer Vision.  93(2).  201-225.
  • Anderson A, Bramen J, Douglas PK, Lenartowicz A, Cho A, Culbertson C, Brody AL, Yuille AL, Cohen MS (2011).  Large sample group independent component analysis of functional magnetic resonance imaging using anatomical atlas-based reduction and bootstrapped clustering.  International Journal of Imaging Systems and Technology.  21(2).  223-231.
  • Douglas PK, Harris S, Yuille A, Cohen MS (2011).  Performance comparison of machine learning algorithms and number of independent components used in fMRI decoding of belief vs. disbelief.  NeuroImage.  56(2).  544-553.
  • Zhu L, Chen Y, Lin C, Yuille A (2011).  Max margin learning of hierarchical configural deformable templates (HCDTs) for efficient object parsing and pose estimation.  International Journal of Computer Vision.  93(1).  1-21.
  • Papandreou G, Yuille AL (2010).  Gaussian sampling by local perturbations.  Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010, NIPS 2010.
  • Lu H, Lin T, Lee ALF, Vese L, Yuille A (2010).  Functional form of motion priors in human motion perception.  Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010, NIPS 2010.
  • Wu S, He X, Lu H, Yuille A (2010).  A unified model of short-range and long-range motion perception.  Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010, NIPS 2010.
  • Zheng S, Yuille A, Tu Z (2010).  Detecting object boundaries using low-, mid-, and high-level information.  Computer Vision and Image Understanding.  114(10).  1055-1067.
  • Zhu L, Chen Y, Yuille A, Freeman W (2010).  Latent hierarchical structural learning for object detection.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  1062-1069.
  • Zhu L, Chen Y, Torralba A, Freeman W, Yuille A (2010).  Part and appearance sharing: Recursive compositional models for multi-view multi-object detection.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  1919-1926.
  • Yuille A (2010).  An information theory perspective on computational vision.  Frontiers of Electrical and Electronic Engineering in China.  5(3).  329-346.
  • Zhu L, Chen Y, Yuille A (2010).  Learning a hierarchical deformable template for rapid deformable object parsing.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  32(6).  1029-1043.
  • Anderson A, Dinov ID, Sherin JE, Quintana J, Yuille AL, Cohen MS (2010).  Classification of spatially unaligned fMRI scans.  NeuroImage.  49(3).  2509-2519.
  • He X, Yuille A (2010).  Occlusion boundary detection using pseudo-depth.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  6314 LNCS(PART 4).  539-552.
  • Chen Y, Zhu L, Yuille A (2010).  Active mask hierarchies for object detection.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  6315 LNCS(PART 5).  43-56.
  • Yuille A, Zheng S (2009).  Compositional noisy-logical learning.  Proceedings of the 26th International Conference On Machine Learning, ICML 2009.  1209-1216.
  • Yuille A, Lu H (2009).  The noisy-logical distribution and its application to causal inference.  Advances in Neural Information Processing Systems 20 - Proceedings of the 2007 Conference.
  • Wu S, Lu H, Lee A, Yuille A (2009).  Motion integration using competitive priors.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  5604 LNCS.  235-258.
  • Lu H, Weiden M, Yuille A (2009).  Modeling the spacing effect in sequential category learning.  Advances in Neural Information Processing Systems 22 - Proceedings of the 2009 Conference.  1159-1167.
  • Chen Y, Zhu L, Lin C, Yuille A, Zhang H (2009).  Rapid inference on a novel AND/OR graph for object detection, segmentation and parsing.  Advances in Neural Information Processing Systems 20 - Proceedings of the 2007 Conference.
  • Wu S, Lu H, Yuille A (2009).  Model selection and velocity estimation using novel priors for motion patterns.  Advances in Neural Information Processing Systems 21 - Proceedings of the 2008 Conference.  1793-1800.
  • Cremers D, Rosenhahn B, Yuille A, Schmidt FR (2009).  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): Preface.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  5604 LNCS.
  • Zhu L, Chen Y, Lin Y, Lin C, Yuille A (2009).  Recursive segmentation and recognition templates for 2D parsing.  Advances in Neural Information Processing Systems 21 - Proceedings of the 2008 Conference.  1985-1992.
  • Kokkinos I, Yuille A (2009).  Inference and learning with hierarchical compositional models.  2009 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2009.  6.
  • Yuille A, Zheng S (2009).  Compositional noisy-logical learning.  ACM International Conference Proceeding Series.  382.
  • Chen Y, Zhu L, Yuille A, Zhang HJ (2009).  Unsupervised learning of probabilistic object models (POMs) for object classification, segmentation, and recognition using knowledge propagation.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  31(10).  1747-1774.
  • Jung M, Chung G, Sundaramoorthi G, Vese LA, Yuille AL (2009).  Sobolev gradients and joint variational image segmentation, denoising and deblurring.  Proceedings of SPIE - The International Society for Optical Engineering.  7246.
  • Kokkinos I, Yuille A (2009).  HOP: Hierarchical object parsing.  2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPR Workshops 2009.  2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  802-809.
  • Zhu L, Chen Y, Yuille A (2009).  Unsupervised learning of probabilistic grammar-Markov models for object categories.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  31(1).  114-128.
  • Corso JJ, Tu Z, Yuille A (2008).  MRF labeling with a graph-shifts algorithm.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  4958 LNCS.  172-184.
  • Zhu L, Lin C, Huang H, Chen Y, Yuille A (2008).  Unsupervised structure learning: Hierarchical recursive composition, suspicious coincidence and competitive exclusion.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  5303 LNCS(PART 2).  759-773.
  • Lu H, Yuille AL, Liljeholm M, Cheng PW, Holyoak KJ (2008).  Bayesian Generic Priors for Causal Learning.  Psychological Review.  115(4).  955-984.
  • Zhu L, Chen Y, Lu Y, Lin C, Yuille A (2008).  Max margin and/or graph learning for parsing the human body.  26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR.
  • Chen Y, Yuille A, Zhu L, Zhang H (2008).  Unsupervised learning of Probabilistic Object Models (POMs) for object classification, segmentation and recognition.  26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR.
  • Zhu L, Ye X, Chen Y, Yuille A (2008).  Structure-perceptron learning of a hierarchical log-linear model.  26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR.
  • Kokkinos I, Yuille A (2008).  Scale invariance without scale selection.  26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR.
  • Corso JJ, Yuille A, Tu Z (2008).  Graph-shifts: Natural image labeling by dynamic hierarchical computing.  26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR.
  • Dube S, Corso JJ, Yuille A, Cloughesy TF, El-Saden S, Sinha U (2008).  Hierarchical segmentation of malignant Gliomas via integrated contextual filter response.  Progress in Biomedical Optics and Imaging - Proceedings of SPIE.  6914.
  • Corso JJ, Sharon E, Dube S, El-Saden S, Sinha U, Yuille A (2008).  Efficient multilevel brain tumor segmentation with integrated bayesian model classification.  IEEE Transactions on Medical Imaging.  27(5).  629-640.
  • Tu Z, Zheng S, Yuille A (2008).  Shape matching and registration by data-driven EM.  Computer Vision and Image Understanding.  109(3).  290-304.
  • Corso JJ, Tu Z, Yuille A, Toga A (2007).  Segmentation of sub-cortical structures by the graph-shifts algorithm.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  4584 LNCS.  183-197.
  • Zhu L, Chen Y, Yuille A (2007).  Unsupervised learning of a probabilistic grammar for object detection and parsing.  Advances in Neural Information Processing Systems.  1617-1624.
  • Corso JJ, Yuille A, Sicotte NL, Toga A (2007).  Detection and segmentation of pathological structures by the extended graph-shifts algorithm.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  4791 LNCS(PART 1).  985-993.
  • Kokkinos I, Yuille A (2007).  Unsupervised learning of object deformation models.  Proceedings of the IEEE International Conference on Computer Vision.
  • Dube S, Corso JJ, Cloughesy TF, El-Saden S, Yuille AL, Sinha U (2007).  Automated MR image processing and analysis of malignant brain tumors: Enabling technology for data mining.  AIP Conference Proceedings.  953.  64-84.
  • Yuille A, Zhu SC, Cremers D, Wang Y (2007).  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics: Preface.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  4679 LNCS.
  • Zheng S, Tu Z, Yuille AL (2007).  Detecting object boundaries using low-, mid-, and high-level information.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
  • Tu Z, Zheng S, Yuille AL, Reiss AL, Dutton RA, Lee AD, Galaburda AM, Dinov I, Thompson PM, Toga AW (2007).  Automated extraction of the cortical sulci based on a supervised learning approach.  IEEE Transactions on Medical Imaging.  26(4).  541-552.
  • Kokkinos I, Maragos P, Yuille A (2006).  Bottom-up & top-down object detection using primal sketch features and graphical models.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  2.  1893-1900.
  • Rokers B, Yuille A, Liu Z (2006).  The perceived motion of a stereokinetic stimulus.  Vision Research.  46(15).  2375-2387.
  • Chater N, Tenenbaum JB, Yuille A (2006).  Probabilistic models of cognition: where next?.  Trends in Cognitive Sciences.  10(7).  292-293.
  • Chater N, Tenenbaum JB, Yuille A (2006).  Probabilistic models of cognition: Conceptual foundations.  Trends in Cognitive Sciences.  10(7).  287-291.
  • Yuille A, Kersten D (2006).  Vision as Bayesian inference: analysis by synthesis?.  Trends in Cognitive Sciences.  10(7).  301-308.
  • Zheng S, Tu Z, Yuille AL, Reiss AL, Dutton RA, Lee AD, Galaburda AM, Thompson PM, Dinov I, Toga AW (2006).  A learning based algorithm for automatic extraction of the cortical sulci.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  4190 LNCS - I.  695-703.
  • Corso JJ, Sharon E, Yuille A (2006).  Multilevel segmentation and integrated bayesian model classification with an application to brain tumor segmentation.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  4191 LNCS - II.  790-798.
  • Yuille A (2005).  Augmented Rescorla-Wagner and Maximum Likelihood estimation.  Advances in Neural Information Processing Systems.  1561-1568.
  • Zhu L, Yuille A (2005).  A hierarchical compositional system for rapid object detection.  Advances in Neural Information Processing Systems.  1633-1640.
  • Rosen-Zvi M, Jordan MI, Yuille AL (2005).  The DLR hierarchy of approximate inference.  Proceedings of the 21st Conference on Uncertainty in Artificial Intelligence, UAI 2005.  493-500.
  • Lu H, Yuille A (2005).  Ideal observers for detecting motion: Correspondence noise.  Advances in Neural Information Processing Systems.  827-834.
  • Tu Z, Chen X, Yuille AL, Zhu SC (2005).  Image parsing: Unifying segmentation, detection, and recognition.  International Journal of Computer Vision.  63(2).  113-140.
  • Yuille A (2005).  The rescorla-wagner algorithm and maximum likelihood estimation of causal parameters.  Advances in Neural Information Processing Systems.
  • Yuille A (2005).  The convergence of contrastive divergences.  Advances in Neural Information Processing Systems.
  • Tu Z, Yuille AL (2004).  Shape matching and recognition using generative models and informative features.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  3023.  195-209.
  • Kersten D, Mamassian P, Yuille A (2004).  Object perception as Bayesian inference.  Annual Review of Psychology.  55.  271-304.
  • Barbu A, Yuille A (2004).  Motion estimation by Swendsen-Wang cuts.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  1.
  • Chen X, Yuille AL (2004).  Detecting and reading text in natural scenes.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  2.
  • Yuille A, Fang F, Schrater P, Kersten D (2004).  Human and ideal observers for detecting image curves.  Advances in Neural Information Processing Systems.
  • Tu Z, Chen X, Yuille AL, Zhu SC (2003).  Image parsing: Unifying segmentation, detection, and recognition.  Proceedings of the IEEE International Conference on Computer Vision.  1.  18-25.
  • Rangarajan A, Coughlan J, Yuille AL (2003).  A Bayesian network framework for relational shape matching.  Proceedings of the IEEE International Conference on Computer Vision.  1.  671-678.
  • Cremers D, Yuille A (2003).  A generative model based approach to motion segmentation.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  2781.  313-320.
  • Yuille AL, Coughlan JM, Konishi S (2003).  The generic viewpoint assumption and planar bias.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  25(6).  775-778.
  • Coughlan JM, Yuille AL (2003).  Manhattan world: Orientation and outlier detection by Bayesian inference.  Neural Computation.  15(5).  1063-1088.
  • Yuille AL, Rangarajan A (2003).  The concave-convex procedure.  Neural Computation.  15(4).  915-936.
  • Konishi S, Yuille A, Coughlan J (2003).  A statistical approach to multi-scale edge detection.  Image and Vision Computing.  21(1).  37-48.
  • Coughlan J, Yuille A (2003).  Algorithms from statistical physics for generative models of images.  Image and Vision Computing.  21(1).  29-36.
  • Kersten D, Yuille A (2003).  Bayesian models of object perception.  Current Opinion in Neurobiology.  13(2).  150-158.
  • Yuille A, Coughlan JM, Konishi S (2003).  The KGBR viewpoint-lighting ambiguity.  Journal of the Optical Society of America A: Optics and Image Science, and Vision.  20(1).  24-31.
  • Konishi S, Yuille AL, Coughlan JM, Zhu SC (2003).  Statistical edge detection: Learning and evaluating edge cues.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  25(1).  57-74.
  • Coughlan JM, Yuille AL (2002).  Bayesian A* tree search with expected O(N) node expansions: Applications to road tracking.  Neural Computation.  14(8).  1929-1958.
  • Yuille AL (2002).  CCCP algorithms to minimize the Bethe and Kikuchi free energies: Convergent alternatives to belief propagation.  Neural Computation.  14(7).  1691-1722.
  • Yuille AL, Rangarajan A (2002).  The concave-convex procedure (CCCP).  Advances in Neural Information Processing Systems.
  • Rangarajan A, Yuille AL (2002).  MIME: Mutual information minimization and entropy maximization for bayesian belief propagation.  Advances in Neural Information Processing Systems.
  • Yuille AL, Coughlan JM, Konishi S (2001).  The KGBR viewpoint-lighting ambiguity and its resolution by generic constraints.  Proceedings of the IEEE International Conference on Computer Vision.  2.  376-382.
  • Coughlan JM, Yuille AL (2001).  The manhattan world assumption: Regularities in scene statistics which enable Bayesian inference.  Advances in Neural Information Processing Systems.
  • Yuille A (2001).  A double-loop algorithm to minimize the bethe free energy.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  2134.  3-18.
  • Yuille AL, Coughlan JM, Wu Y, Zhu SC (2001).  Order parameters for detecting target curves in images: When does high level knowledge help?.  International Journal of Computer Vision.  41(1-2).  9-33.
  • Yuille AL, Zhu SC, Mumford D (2001).  Introduction by guest editors.  International Journal of Computer Vision.  41(1-2).  7.
  • Zhu SC, Yuille AL, Lanterman AD (2001).  ATR applications of minimax entropy models of texture and shape.  Proceedings of SPIE-The International Society for Optical Engineering.  4379.  574-583.
  • Coughlan J, Yuille A, English C, Snow D (2000).  Efficient deformable template detection and localization without user initialization.  Computer Vision and Image Understanding.  78(3).  303-319.
  • Konishi S, Yuille AL (2000).  Statistical cues for domain specific image segmentation with performance analysis.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  1.  125-132.
  • Burgi PY, Yuille AL, Grzywacz NM (2000).  Probabilistic motion estimation based on temporal coherence.  Neural Computation.  12(8).  1839-1867.
  • Yuille AL, Coughlan JM, Zhu SC (2000).  Unified framework for performance analysis of Bayesian inference.  Proceedings of SPIE - The International Society for Optical Engineering.  4050.  333-346.
  • Yuille AL, Coughlan JM (2000).  An A* perspective on deterministic optimization for deformable templates.  Pattern Recognition.  33(4).  603-616.
  • Yuille AL, Coughlan J, Zhu SC, Wu Y (2000).  Order parameters for minimax entropy distributions: When does high level knowledge help?.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  1.  558-565.
  • Yuille AL (2000).  Fundamental limits of Bayesian inference: Order parameters and phase transitions for road tracking.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  22(2).  160-173.
  • Belhumeur PN, Kriegman DJ, Yuille AL (1999).  Bas-relief ambiguity.  International Journal of Computer Vision.  35(1).  33-44.
  • Coughlan JM, Yuille AL (1999).  Manhattan World: Compass direction from a single image by Bayesian inference.  Proceedings of the IEEE International Conference on Computer Vision.  2.  941-947.
  • Yuille AL, Snow D, Epstein R, Belhumeur PN (1999).  Determining generative models of objects under varying illumination: Shape and albedo from multiple images using SVD and integrability.  International Journal of Computer Vision.  35(3).  203-222.
  • Rangarajan A, Yuille A, Mjolsness E (1999).  Convergence properties of the softassign quadratic assignment algorithm.  Neural Computation.  11(6).  1455-1474.
  • Yuille AL, Coughlan J (1999).  High-level and generic models for visual search: When does high level knowledge help?.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  2.  631-637.
  • Konishi S, Yuille AL, Coughlan J, Zhu SC (1999).  Fundamental bounds on edge detection: An information theoretic evaluation of different edge cues.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  1.  573-579.
  • Yuille AL, Coughlan JM (1999).  Convergence rates of algorithms for visual search: Detecting visual contours.  Advances in Neural Information Processing Systems.  641-647.
  • Coughlan JM, Yuille AL (1999).  A phase space approach to minimax entropy learning and the minutemax approximations.  Advances in Neural Information Processing Systems.  761-767.
  • Coughlan JM, Yuille AL (1999).  Bayesian a* Tree search with expected o(N) convergence rates for road tracking.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  1654.  189-204.
  • Belhumeur PN, Kriegman DJ, Yuille AL (1999).  Shadows, shading, and projective ambiguity.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  1681.  132-151.
  • Coughlan J, Yuille A, English C, Snow D (1998).  Efficient optimization of a deformable template using dynamic programming.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  747-752.
  • Yuille AL, Burgi PY, Grzywacz NM (1998).  Visual motion estimation and prediction: A probabilistic network model for temporal coherence.  Proceedings of the IEEE International Conference on Computer Vision.  973-978.
  • Yuille AL, Snow D, Nitzberg M (1998).  Signfinder: Using color to detect, localize and identify informational signs.  Proceedings of the IEEE International Conference on Computer Vision.  628-633.
  • Yuille AL, Ferraro M, Zhang T (1998).  Image Warping for Shape Recovery and Recognition.  Computer Vision and Image Understanding.  72(3).  351-359.
  • Yuille AL, Coughlan J (1997).  Twenty questions, focus of attention, and a*: A theoretical comparison of optimization strategies.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  1223.  197-212.
  • Yuille AL, Ferraro M, Zhang T (1997).  Relating image warping to 3D geometrical deformations.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  1310.  361-368.
  • Belhumeur PN, Kriegman DJ, Yuille AL (1997).  Bas-relief ambiguity.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  1060-1066.
  • Yuille A, Ferraro M, Zhang T (1997).  Surface shape from warping.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  846-851.
  • Rangarajan A, Yuille A, Gold S, Mjolsness E (1997).  A convergence proof for the softassign quadratic assignment algorithm.  Advances in Neural Information Processing Systems.  620-626.
  • Yuille A, Snow D (1997).  Shape and albedo from multiple images using integrability.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  158-164.
  • Bülthoff HH, Yuille AL (1996).  A Bayesian framework for the integration of visual modules.  Attention and Performance.  16.  47-70.
  • Zhu SC, Yuille AL (1996).  FORMS: A flexible object recognition and modelling system.  International Journal of Computer Vision.  20(2).  187-212.
  • Song CZ, Yuille AL (1996).  FORMS: A flexible object recognition and modelling system.  International Journal of Computer Vision.  20(3).  187-212.
  • Epstein R, Yuille AL, Belhumeur PN (1996).  Learning object representations from lighting variations.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  1144.  179-199.
  • Yuille AL, Kolodny JA, Lee CW (1996).  Dimension reduction, generalized deformable models and the development of ocularity and orientation.  Neural Networks.  9(2).  309-319.
  • Geiger D, Ladendorf B, Yuille A (1995).  Occlusions and binocular stereo.  International Journal of Computer Vision.  14(3).  211-226.
  • Epstein R, Hallinan PW, Yuille AL (1995).  5±2 eigenimages suffice: an empirical investigation of low-dimensional lighting models.  108-116.
  • Zhu SC, Yuille AL (1995).  FORMS: a flexible object recognition and modelling system.  IEEE International Conference on Computer Vision.  465-472.
  • Xu L, Yuille AL (1995).  Robust Principal Component Analysis by Self-Organizing Rules Based on Statistical Physics Approach.  IEEE Transactions on Neural Networks.  6(1).  131-143.
  • Zhu SC, Lee TS, Yuille AL (1995).  Region competition: unifying snakes, region growing, energy/bayes/MDL for multi-band image segmentation.  IEEE International Conference on Computer Vision.  416-423.
  • Belhumeur PN, Yuille AL (1995).  Recovering object surfaces from viewed changes in surface texture patterns.  IEEE International Conference on Computer Vision.  876-881.
  • Weisman MJ, Yuille AL, Clark JJ (1995).  Parameterized surface fitting via MAP estimation for binocular stereo.  Proceedings - IEEE International Conference on Robotics and Automation.  2.  2049-2053.
  • Yuille AL, Smirnakis SM, Xu L (1995).  Bayesian self-organization driven by prior probability distributions.  Neural Computation.  7(3).  580-593.
  • Yang Y, Yuille AL (1995).  Multilevel enhancement and detection of stereo disparity surfaces.  Artificial Intelligence.  78(1-2).  121-145.
  • Xu L, Krzyzak A, Yuille A (1994).  On radial basis function nets and kernel regression: Statistical consistency, convergence rates, and receptive field size.  Neural Networks.  7(4).  609-628.
  • Matsugu M, Yuille AL (1994).  Spatiotemporal information storage in a content addressable memory using realistic neurons.  Neural Networks.  7(3).  419-439.
  • Epstein R, Yuille A (1994).  Training a general purpose deformable template.  Proceedings - International Conference on Image Processing, ICIP.  1.  203-207.
  • Zhu SC, Yuille AL (1994).  A framework for shape representation and recognition.  Proceedings - International Conference on Image Processing, ICIP.  1.  671-675.
  • Kosowsky JJ, Yuille AL (1994).  The invisible hand algorithm: Solving the assignment problem with statistical physics.  Neural Networks.  7(3).  477-490.
  • Yang Y, Yuille A, Lu J (1993).  Local, global and multilevel stereo matching.  IEEE Computer Vision and Pattern Recognition.  274-278.
  • Elfadel IM, Yuille AL (1993).  Mean-field phase transitions and correlation functions for Gibbs random fields.  Journal of Mathematical Imaging and Vision.  3(2).  167-186.
  • Clark JJ, Weisman MJ, Yuille AL (1993).  Using viewpoint consistency in active stereo vision.  Proceedings of SPIE - The International Society for Optical Engineering.  1825.  696-702.
  • Xu L, Krzyzak A, Yuille A (1993).  On radial basis function net and kernel regression. Approximation ability, convergence rate and receptive field size.  Proceedings of the 1993 IEEE International Symposium on Information Theory.  353.
  • Watamaniuk SNJ, Grzywacz NM, Yuille AL (1993).  Dependence of speed and direction perception on cinematogram dot density.  Vision Research.  33(5-6).  849-859.
  • Elfadel IM, Yuille AL (1992).  Mean-field phase transitions for Gibbs random fields.  Proceedings of SPIE - The International Society for Optical Engineering.  1766.  257-268.
  • Yang Y, Yuille A (1992).  Grouping iso-velocity points for ego-motion recovery.  Proceedings Tenth National Conference on Artificial Intelligence.  356-361.
  • Yuille A, Vincent L, Geiger D (1992).  Statistical morphology and Bayesian reconstruction.  Journal of Mathematical Imaging and Vision.  1(3).  223-238.
  • Yuille AL, Hallinan PW, Cohen DS (1992).  Feature extraction from faces using deformable templates.  International Journal of Computer Vision.  8(2).  99-111.
  • Lee TS, Mumford D, Yuille A (1992).  Texture segmentation by minimizing vector-valued energy functionals: The coupled-membrane model.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  588 LNCS.  165-173.
  • Geiger D, Ladendorf B, Yuille A (1992).  Occlusions and binocular stereo.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  588 LNCS.  425-433.
  • Ohlsson M, Peterson C, Yuille AL (1992).  Track finding with deformable templates - the elastic arms approach.  Computer Physics Communications.  71(1-2).  77-98.
  • Yuille AL, Kolodny JA, Lee CW (1992).  Dimension reduction, generalized deformable models and the development of occularity and orientation.  Proceedings. IJCNN - International Joint Conference on Neural Networks.  597-602.
  • Yang Y, Yuille A (1991).  Sources from shading.  534-539.
  • Kosowsky JJ, Yuille AL (1991).  Solving the assignment problem with statistical physics.  Proceedings. IJCNN-91-Seattle: International Joint Conference on Neural Networks.  159-164.
  • Yuille AL, Honda K, Peterson C (1991).  Particle tracking by deformable templates.  Proceedings. IJCNN-91-Seattle: International Joint Conference on Neural Networks.  7-12.
  • Elfadel IM, Yuille AL (1991).  Mean-field theory for grayscale texture synthesis using Gibbs random fields.  Proceedings of SPIE - The International Society for Optical Engineering.  1569.  248-259.
  • Yuille A, Peterson C, Ilonda K (1991).  Deformable templates, robust statistics and hough transforms.  Proceedings of SPIE - The International Society for Optical Engineering.  1570.  166-174.
  • Geiger D, Yuille A (1991).  A common framework for image segmentation.  International Journal of Computer Vision.  6(3).  227-243.
  • Yuille AL, Geiger D, Bülthoff HH (1991).  Stereo integration, mean Field theory and psychophysics.  Network: Computation in Neural Systems.  2(4).  423-442.
  • Gennert M, Ren B, Yuille AL (1991).  Stereo matching by energy function minimization.  Proceedings of SPIE - The International Society for Optical Engineering.  1385.  268-279.
  • Yuille AL, Vincent LM, Geiger D (1991).  Statistical morphology.  Proceedings of SPIE - The International Society for Optical Engineering.  1568.  271-282.
  • Bulthoff HH, Yuille AL (1991).  Shape-from-X. Psychophysics and computation.  Proceedings of SPIE - The International Society for Optical Engineering.  1383.  235-246.
  • Yuille AL (1991).  Deformable templates for face recognition.  Journal of Cognitive Neuroscience.  3(1).  59-70.
  • Lipson P, Yuille AL, O'Keeffe D, Cavanaugh J, Taaffe J, Rosenthal D (1990).  Automated bone density calculation using feature extraction by deformable templates.  Proceedings of the First Conference on Visualization in Biomedical Computing.  477-484.
  • Geiger D, Yuille A (1990).  A common framework for image segmentation.  Proceedings - International Conference on Pattern Recognition.  1.  502-507.
  • Clark JJ, Yuille AL (1990).  Shape from shading via the fusion of specular and Lambertian image components.  Proceedings - International Conference on Pattern Recognition.  1.  88-92.
  • Yuille A, Geiger D (1990).  Stereo and controlled movement.  International Journal of Computer Vision.  4(2).  141-152.
  • Grzywacz NM, Yuille AL (1990).  A model for the estimate of local velocity.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  427 LNCS.  331-335.
  • Lipson P, Yuille AL, O’Keeffe D, Cavanaugh J, Taaffe J, Rosenthal D (1990).  Deformable templates for feature extraction from medical images.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  427 LNCS.  413-417.
  • Grzywacz NM, Yuille AL (1990).  A model for the estimate of local image velocity by cells in the visual cortex.  Proceedings of the Royal Society B: Biological Sciences.  239(1295).  129-161.
  • Yuille A, Leyton M (1990).  3D symmetry-curvature duality theorems.  Computer vision, graphics, and image processing.  52(1).  124-140.
  • Yuille AL, Geiger D, Bülthoff H (1990).  Stereo integration, mean field theory and psychophysics.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  427 LNCS.  73-82.
  • Hwang Tl, Clark JJ, Yuille AL (1989).  Depth recovery algorithm using defocus information.  476-482.
  • Geiger D, Yuille A (1989).  Stereo and eye movement.  Biological Cybernetics.  62(2).  117-128.
  • Grzywacz NM, Smith JA, Yuille AL (1989).  Common theoretical framework for visual motion's spatial and temporal coherence..  148-155.
  • Yuille AL, Cohen DS, Hallinan PW (1989).  Feature extraction from faces using deformable templates.  104-109.
  • Yuille AL, Kammen DM, Cohen DS (1989).  Quadrature and the development of orientation selective cortical cells by Hebb rules.  Biological Cybernetics.  61(3).  183-194.
  • Yuille AL, Grzywacz NM (1989).  A mathematical analysis of the motion coherence theory.  International Journal of Computer Vision.  3(2).  155-175.
  • Yuille AL (1989).  Energy functions for early vision and analog networks.  Biological Cybernetics.  61(2).  115-123.
  • Yuille AL (1989).  Zero crossings on lines of curvature.  Computer Vision, Graphics and Image Processing.  45(1).  68-87.
  • Jasinschi R, Yuille A (1989).  Nonrigid motion and regge calculus.  Journal of the Optical Society of America A: Optics and Image Science, and Vision.  6(7).  1088-1095.
  • Gennert MA, Yuille AL (1988).  Determining the optimal weights in multiple objective function optimization.  87-89.
  • Yuille AL, Grzywacz NM (1988).  Motion coherence theory.  344-353.
  • Yuille AL (1988).  Creation of structure in dynamic shape.  685-689.
  • Kammen DM, Yuille AL (1988).  Spontaneous symmetry-breaking energy functions and the emergence of orientation selective cortical cells.  Biological Cybernetics.  59(1).  23-31.
  • Yuille AL, Kammen DM (1988).  Spontaneous symmetry-breaking energy functions, orientation selective cortical cells, and hypercolumnar cell assemblies.  Neural Networks.  1(1 SUPPL).  153.
  • Grzywacz NM, Yuille AL (1988).  Massively parallel implementations of theories for apparent motion..  Spatial vision.  3(1).  15-44.
  • Verri A, Yuille A (1988).  Some perspective projection invariants.  Journal of the Optical Society of America A: Optics and Image Science, and Vision.  5(3).  426-431.
  • Poggio T, Voorhees H, Yuille A (1988).  A regularized solution to edge detection.  Journal of Complexity.  4(2).  106-123.
  • Yuille AL, Grzywacz NM (1988).  A computational theory for the perception of coherent visual motion.  Nature.  333(6168).  71-74.
  • Yuille A (1987).  A method for computing spectral reflectance.  Biological Cybernetics.  56(2-3).  195-201.
  • Geiger D, Yuille A (1987).  STEREOPSIS AND EYE-MOVEMENT..  306-314.
  • Yuille A, Leighton M (1987).  3D SYMMETRY-CURVATURE DUALITY THEOREMS..  721-726.
  • Yuille AL, Poggio TA (1986).  Scaling Theorems for Zero Crossings.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  PAMI-8(1).  15-25.
  • Koch C, Marroquin J, Yuille A (1986).  Analog 'neuronal' networks in early vision.  Proceedings of the National Academy of Sciences of the United States of America.  83(12).  4263-4267.
  • Brady M, Ponce J, Yuille A, Asada H (1985).  DESCRIBING SURFACES..  5-16.
  • Brady M, Yuille A (1985).  REPRESENTING THREE-DIMENSIONAL SHAPE..  261-270.
  • Yuille AL, Poggio T (1985).  Fingerprints theorems for zero crossings.  Journal of the Optical Society of America A: Optics and Image Science, and Vision.  2(5).  683-692.
  • Brady M, Ponce J, Yuille A, Asada H (1985).  Describing surfaces..  Computer Vision, Graphics, & Image Processing.  32(1).  1-28.
  • Yuille AL (1984).  SMOOTHEST VELOCITY FIELD TOKEN MATCHING SCHEMES..  621-630.
  • Yuille AL, Poggio T (1984).  SCALING THEOREMS FOR ZERO-CROSSINGS..  3-7.
  • Brady M, Yuille A (1984).  An Extremum Principle for Shape from Contour.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  PAMI-6(3).  288-301.
  • Yuille AL, Poggio T (1983).  FINGERPRINTS THEOREMS..  362-365.
  • Brady M, Yuille A (1983).  EXTREMUM PRINCIPLE FOR SHAPE FROM CONTOUR..  2.  969-972.
Books
  • George Papandreou, Daniel Tarlow, eds, Yuille AL (2016).  Perturb-and-MAP Random Fields.  Perturbations, Optimization, and Statistics.
  • Yuille AL, P.W. Hallinan, G. Gordon, P.J. Giblin, P.J. Giblin (1999).  3. Two- and Three- Dimensional Patterns of the Face.  Research Monograph.  A K Peters, Ltd.
  • Eds. A. Blake, Yuille AL (1992).  2. Active Vision.  MIT Press.
  • J.J. Clark, Yuille AL (1990).  1. Data Fusion for Sensory Information Processing Systems.  Kluwer Academic Publishers.
Book Chapters
  • Zhou Y, Yu Q, Wang Y, Xie L, Shen W, Fishman EK, Yuille AL (2019).  2D-Based Coarse-to-Fine Approaches for Small Target Segmentation in Abdominal CT Scans.  Advances in Computer Vision and Pattern Recognition.  43-67.
  • Li Y, Zhu Z, Zhou Y, Xia Y, Shen W, Fishman EK, Yuille AL (2019).  Volumetric Medical Image Segmentation: A 3D Deep Coarse-to-Fine Framework and Its Adversarial Examples.  Advances in Computer Vision and Pattern Recognition.  69-91.
  • Qiu W, Wang X, Bai X, Yuille A, Tu Z (2015).  Scale-space sift flow.  Dense Image Correspondences for Computer Vision.  71-82.
  • Griffiths TL, Yuille A (2012).  A primer on probabilistic inference.  The Probabilistic Mind: Prospects for Bayesian cognitive science.
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