Faculty

Donald Geman

Professor

Research Interests

  • Image Analysis
  • Statistical Learning
  • Bioinformatics

Donald Geman, a professor of applied mathematics and statistics, works at the foundation of widely used methods in machine vision, machine learning and transcription-based cancer phenotyping. He is a member of Johns Hopkins’ Center for Imaging Science and its Institute for Computational Medicine. He also is a visiting professor with École Normale Supérieure de Cachan and INRIA in France.

Geman is recognized for his work in stochastic processes, image analysis, machine learning and computational medicine. He is best known for his work on occupation densities for random functions, Markov random fields for image processing, and for introducing the Gibbs Sampler algorithm for Bayesian computation and randomized decision trees for classification.

He has made seminal contributions across multiple fields in applied mathematical sciences. His idea of randomized query selection (aka “random forests”) has become one of the most widely used classification methods in computational vision and biology, and the computational basis of Microsoft’s Kinect vision system. Geman also pioneered a “twenty questions” approach to pattern recognition that is the basis for diverse systems like road tracking and face detection. He proposed a highly novel method for predicting cancer phenotypes, including diagnosis, prognosis, and prediction of treatment response, from messenger RNA (mRNA) concentrations.

In work published in the Proceedings of the National Academy of Sciences in 2018, Geman and colleagues described a method to simplify complex biomolecular data about tumors, in principle making it easier to prescribe appropriate treatments for specific patients. The computational strategy transforms highly complex information into a simplified format that emphasizes patient-to-patient variation in the molecular signatures of cancer cells. Geman’s team found a way to greatly simplify the data on tens of thousands of molecular states by converting these data to binary labels, indicating whether a measurement falls within or beyond healthy levels.

His current projects in computational biology are driven by the objective of tailoring cancer treatment to an individual molecular profile by extracting information from gigantic amounts of data about normal functioning and abnormal perturbations in biological networks. These data are accumulated by new sequencing technologies and enable his group to learn algorithms to predict disease phenotypes, progression and treatment response for individuals.

He is a member of the National Academy of Sciences and a Fellow of the Society for Industrial and Applied Mathematics (SIAM) and the Institute of Mathematical Statistics (IMS).

Geman earned a BA in English literature from Northern Illinois University in 1965 and a PhD in mathematics from Northwestern University in 1970. He worked for the University of Massachusetts’ Department of Mathematics and Statistics from 1970 to 2001, before joining the faculty of the Whiting School of Engineering.

Education
  • Ph.D. 1970, Northwstrn University*
  • Bachelor of Arts 1965, Univ Illinois Urbana
Experience
  • 2012 - Present:  Chair, Board of Review, Academic Council
  • 2007 - 2007:  Founder, BME/AMS
  • 2006 - 2007:  Chair, SIAM Activity Group, Imaging Science
Research Areas
  • COMPUTER vision
  • Computational Biology
  • Computational Molecular Medicine
  • Statistical Learning
Awards
  • 2015:  Member
  • 2011:  Fellow - SIAM (Society for Industrial and Applied Mathematicians)
  • 1998:  Fellow - IMS (Institute of Mathematical Statistics)
Journal Articles
  • Kushnarev S, Qiu A, Younes L (2020).  Preface.  Lecture Notes Series, Institute for Mathematical Sciences.  37.  IX-X.
  • Tang X, Ross CA, Johnson H, Paulsen JS, Younes L, Albin RL, Ratnanather JT, Miller MI (2019).  Regional subcortical shape analysis in premanifest Huntington's disease.  Human Brain Mapping.  40(5).  1419-1433.
  • Younes L, Albert M, Moghekar A, Soldan A, Pettigrew C, Miller MI (2019).  Identifying changepoints in biomarkers during the preclinical phase of Alzheimer's disease.  Frontiers in Aging Neuroscience.  11(APR).
  • Hsieh DN, Arguillère S, Charon N, Miller MI, Younes L (2019).  A Model for Elastic Evolution on Foliated Shapes.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  11492 LNCS.  644-655.
  • Kulason S, Tward DJ, Brown T, Sicat CS, Liu CF, Ratnanather JT, Younes L, Bakker A, Gallagher M, Albert M, Miller MI (2019).  Cortical thickness atrophy in the transentorhinal cortex in mild cognitive impairment.  NeuroImage: Clinical.  21.  101617.
  • Kushnarev S, Qiu A, Younes L (2019).  Preface.  Lecture Notes Series, Institute for Mathematical Sciences.  37.  IX-X.
  • Hsieh DN, Younes L (2019).  Piecewise Rigid Motion in Diffeomorphism Groups with Strong Right-Invariant Metrics.  Lecture Notes Series, Institute for Mathematical Sciences.  37.  97-114.
  • Ratnanather JT, Arguillère S, Kutten KS, Hubka P, Younes L, Kral A (2019).  3D Normal Coordinate Systems for Cortical Areas.  Lecture Notes Series, Institute for Mathematical Sciences.  37.  167-179.
  • Yushkevich PA, Aly A, Wang J, Xie L, Gorman RC, Younes L, Pouch AM (2019).  Diffeomorphic Medial Modeling.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  11492 LNCS.  208-220.
  • Miller MI, Arguillère S, Tward DJ, Younes L (2018).  Computational anatomy and diffeomorphometry: A dynamical systems model of neuroanatomy in the soft condensed matter continuum.  Wiley Interdisciplinary Reviews: Systems Biology and Medicine.  10(6).
  • Wu D, Faria AV, Younes L, Ross CA, Mori S, Miller MI (2018).  Whole-brain segmentation and change-point analysis of anatomical brain mri—application in premanifest huntington's disease.  Journal of Visualized Experiments.  2018(136).
  • Afsari B, Guo T, Considine M, Florea L, Kagohara LT, Stein-O'Brien GL, Kelley D, Flam E, Zambo KD, Ha PK, Geman D, Ochs MF, Califano JA, Gaykalova DA, Favorov AV, Fertig EJ (2018).  Splice Expression Variation Analysis (SEVA) for inter-tumor heterogeneity of gene isoform usage in cancer.  Bioinformatics.  34(11).  1859-1867.
  • Slama P, Hoopmann MR, Moritz RL, Geman D (2018).  Robust determination of differential abundance in shotgun proteomics using nonparametric statistics.  Molecular Omics.  14(6).  424-436.
  • Wu D, Faria AV, Younes L, Mori S, Brown T, Johnson H, Paulsen JS, Ross CA, Miller MI (2017).  Mapping the order and pattern of brain structural MRI changes using change-point analysis in premanifest Huntington's disease.  Human Brain Mapping.  38(10).  5035-5050.
  • Tang X, Miller MI, Younes L (2017).  Biomarker change-point estimation with right censoring in longitudinal studies.  Annals of Applied Statistics.  11(3).  1738-1762.
  • Staneva V, Younes L (2017).  Learning Shape Trends: Parameter Estimation in Diffusions on Shape Manifolds.  IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops.  2017-July.  717-725.
  • Tward D, Miller M, Trouvé A, Younes L (2017).  Parametric Surface Diffeomorphometry for Low Dimensional Embeddings of Dense Segmentations and Imagery.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  39(6).  1195-1208.
  • Dirlikov B, Younes L, Nebel MB, Martinelli MK, Tiedemann AN, Koch CA, Fiorilli D, Bastian AJ, Denckla MB, Miller MI, Mostofsky SH (2017).  Novel automated morphometric and kinematic handwriting assessment: A validity study in children with ASD and ADHD.  Journal of Occupational Therapy, Schools, and Early Intervention.  10(2).  185-201.
  • Ament SA, Pearl JR, Grindeland A, Claire JS, Earls JC, Kovalenko M, Gillis T, Mysore J, Gusella JF, Lee JM, Kwak S, Howland D, Lee MY, Baxter D, Scherler K, Wang K, Geman D, Carroll JB, MacDonald ME, Carlson G, Wheeler VC, Price ND, Hood LE (2017).  High resolution time-course mapping of early transcriptomic, molecular and cellular phenotypes in Huntington's disease CAG knock-in mice across multiple genetic backgrounds.  Human Molecular Genetics.  26(5).  913-922.
  • Tang X, Albert M, Miller MI, Younes L (2016).  Change point estimation of the hippocampal volumes in Alzheimer's disease.  Proceedings - 2016 13th Conference on Computer and Robot Vision, CRV 2016.  358-361.
  • Geman D, Geman S (2016).  Opinion: Science in the age of selfies.  Proceedings of the National Academy of Sciences.  113(34).  9384-9387.
  • Arguillère S, Miller MI, Younes L (2016).  Diffeomorphic surface registration with atrophy constraints.  SIAM Journal on Imaging Sciences.  9(3).  975-1003.
  • Richardson CL, Younes L (2016).  Metamorphosis of images in reproducing kernel Hilbert spaces.  Advances in Computational Mathematics.  42(3).  573-603.
  • Soldan A, Pettigrew C, Cai Q, Wang MC, Moghekar AR, O'Brien RJ, Selnes OA, Albert MS, Rodzon B, Gottesman R, Sacktor N, McKhann G, Turner S, Farrington L, Grega M, Rudow G, D'Agostino D, Rudow S, Miller M, Mori S, Ratnanather T, Brown T, Chi H, Kolasny A, Oishi K, Reigel T, Younes L, Spangler A, Scherer R, Shade D, Ervin A, Jones J, Toepfner M, Parlett L, Patterson A, Mohammed A, Lu D, Troncoso J, Crain B, Pletnikova O, Fisher K (2016).  Hypothetical preclinical Alzheimer disease groups and longitudinal cognitive change.  JAMA Neurology.  73(6).  698-705.
  • Ardekani S, Jain S, Sanzi A, Corona-Villalobos CP, Abraham TP, Abraham MR, Zimmerman SL, Wu KC, Winslow RL, Miller MI, Younes L (2016).  Shape analysis of hypertrophic and hypertensive heart disease using MRI-based 3D surface models of left ventricular geometry.  Medical Image Analysis.  29.  12-23.
  • Arguillère S, Trélat E, Trouvé A, Younes L (2016).  Registration of multiple shapes using constrained optimal control.  SIAM Journal on Imaging Sciences.  9(1).  344-385.
  • Jain S, Salimpour Y, Younes L, Smith G, Mari Z, Sossi V, Rahmim A (2016).  Application of pattern recognition framework for quantification of Parkinson's disease in DAT SPECT imaging.  2014 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2014.
  • Mittal R, Seo JH, Vedula V, Choi YJ, Liu H, Huang HH, Jain S, Younes L, Abraham T, George RT (2016).  Computational modeling of cardiac hemodynamics: Current status and future outlook.  Journal of Computational Physics.  305.  1065-1082.
  • Faria AV, Ratnanather JT, Tward DJ, Lee DS, Van Den Noort F, Wu D, Brown T, Johnson H, Paulsen JS, Ross CA, Younes L, Miller MI (2016).  Linking white matter and deep gray matter alterations in premanifest Huntington disease.  NeuroImage: Clinical.  11.  450-460.
  • Miller MI, Trouvé A, Younes L (2015).  Hamiltonian Systems and Optimal Control in Computational Anatomy: 100 Years since D'Arcy Thompson.  Annual Review of Biomedical Engineering.  17.  447-509.
  • Vedula V, George R, Younes L, Mittal R (2015).  Hemodynamics in the left atrium and its effect on ventricular flow patterns.  Journal of Biomechanical Engineering.  137(11).
  • Marchionni L, Geman D (2015).  Abstract 3754: Predicting cancer phenotypes with mechanism-driven multi-omics data integration.  Cancer Research.  75(15 Supplement).  3754-3754.
  • Chang LB, Geman D (2015).  Tracking Cross-Validated Estimates of Prediction Error as Studies Accumulate.  Journal of the American Statistical Association.  110(511).  1239-1247.
  • Soldan A, Pettigrew C, Lu Y, Wang MC, Selnes O, Albert M, Brown T, Ratnanather JT, Younes L, Miller MI, Rodzon B, Gottesman R, Sacktor N, McKhann G, Turner S, Farrington L, Grega M, D'Agostino D, Feagen S, Dolan D, Dolan H, Mori S, Kolasny A, Oishi K, Schneider W, O'Brien R, Moghekar A, Spangler A, Scherer R, Meinert C, Shade D, Ervin A, Jones J, Toepfner M, Parlett L, Patterson A, Lassiter L, Cai Q, Troncoso J, Crain B, Pletnikova O, Rudow G, Fisher K, Cernansky J, Holtzman D, Knopman D, Kukull W, McArdle J, Buckholtz N, Hsiao J, Ryan L, Evans J (2015).  Relationship of medial temporal lobe atrophy, APOE genotype, and cognitive reserve in preclinical Alzheimer's disease.  Human Brain Mapping.  36(7).  2826-2841.
  • Tang X, Holland D, Dale AM, Younes L, Miller MI (2015).  The diffeomorphometry of regional shape change rates and its relevance to cognitive deterioration in mild cognitive impairment and Alzheimer's disease.  Human Brain Mapping.  36(6).  2093-2117.
  • Geman D, Ochs M, Price ND, Tomasetti C, Younes L (2015).  An argument for mechanism-based statistical inference in cancer.  Human Genetics.  134(5).  479-495.
  • Geman D, Geman S, Hallonquist N, Younes L (2015).  Visual Turing test for computer vision systems.  Proceedings of the National Academy of Sciences of the United States of America.  112(12).  3618-3623.
  • Rejeb Sfar A, Boujemaa N, Geman D (2015).  Confidence Sets for Fine-Grained Categorization and Plant Species Identification.  International Journal of Computer Vision.  111(3).  255-275.
  • Afsari B, Fertig EJ, Geman D, Marchionni L (2015).  SwitchBox: An R package for k-Top Scoring Pairs classifier development.  Bioinformatics.  31(2).  273-274.
  • Marchionni L, Geman D (2015).  Predicting cancer phenotypes with mechanism-driven multi-omics data integration.  Cancer Research.  75(15 Supplement).  3754-3754.
  • Sfar AR, Boujemaa N, Geman D (2015).  Confidence sets for fine-grained categorization and plant species identification.  International Journal of Computer Vision.  111(3).  255-275.
  • Afsari B, Fertig EJ, Geman D, Marchionni L (2015).  switchBox: an R package for k-Top Scoring Pairs classifier development.  Bioinformatics.  31(2).  273-274.
  • Chang L, Geman D (2015).  Tracking cross-validated estimates of prediction error as studies accumulate.  Journal of the American Statistical Association.  110(511).  1239-1247.
  • Geman D, Geman S, Hallonquist N, Younes L (2015).  Visual turing test for computer vision systems.  Proceedings of the National Academy of Sciences.  112(12).  3618-3623.
  • Geman D, Geman H, Taleb NN (2015).  Tail risk constraints and maximum entropy.  Entropy.  17(6).  3724-3737.
  • Mahon PB, Lee DS, Trinh H, Tward D, Miller MI, Younes L, Barta PE, Ratnanather JT (2015).  Morphometry of the amygdala in schizophrenia and psychotic bipolar disorder.  Schizophrenia Research.  164(1-3).  199-202.
  • Geman D, Ochs M, Price ND, Tomasetti C, Younes L (2015).  An argument for mechanism-based statistical inference in cancer.  Human genetics.  134(5).  479-495.
  • Miller MI, Ratnanather JT, Tward DJ, Brown T, Lee DS, Ketcha M, Mori K, Wang MC, Mori S, Albert MS, Younes L, Rodzon B, Selnes O, Gottesman R, Sacktor N, McKhann G, Turner S, Farrington L, Grega M, D'Agostino D, Feagen S, Dolan D, Dolan H, Kolasny A, Schneider W, O'Brien R, Moghekar A, Meehan R, Scherer R, Meinert C, Shade D, Ervin A, Jones J, Toepfner M, Parlett L, Patterson A, Lassiter L, Li S, Lu Y, Troncoso J, Crain B, Pletnikova O, Rudow G, Fisher K (2015).  Network neurodegeneration in Alzheimer's disease via MRI based shape diffeomorphometry and high-field atlasing.  Frontiers in Bioengineering and Biotechnology.  3(MAY).
  • Arguillère S, Trélat E, Trouvé A, Younes L (2015).  Shape deformation analysis from the optimal control viewpoint.  Journal des Mathematiques Pures et Appliquees.  104(1).  139-178.
  • Miller MI, Younes L, Ratnanather JT, Brown T, Trinh H, Lee DS, Tward D, Mahon PB, Mori S, Albert M (2015).  Amygdalar atrophy in symptomatic Alzheimer's disease based on diffeomorphometry: The BIOCARD cohort.  Neurobiology of Aging.  36(S1).  S3-S10.
  • Tang X, Holland D, Dale AM, Younes L, Miller MI (2015).  Baseline shape diffeomorphometry patterns of subcortical and ventricular structures in predicting conversion of mild cognitive impairment to Alzheimer's disease.  Journal of Alzheimer's Disease.  44(2).  599-611.
  • Geman D, Geman H, Taleb NN (2015).  Tail risk constraints and maximum entropy.  Entropy.  17(6).  3724-3737.
  • Geman D, Ochs M, Price ND, Tomasetti C, Younes E (2014).  An argument for mechanism-based statistical inference in cancer..  Human genetics.
  • Ma S, Sung J, Magis AT, Wang Y, Geman D, Price ND (2014).  Measuring the effect of inter-study variability on estimating prediction error.  PLoS ONE.  9(10).
  • Murawski AM, Gurbani S, Harper JS, Klunk M, Younes L, Jain SK, Jedynak BM (2014).  Imaging the evolution of reactivation pulmonary tuberculosis in mice using 18F-FDG PET.  Journal of Nuclear Medicine.  55(10).  1726-1729.
  • Younes L, Ratnanather JT, Brown T, Aylward E, Nopoulos P, Johnson H, Magnotta VA, Paulsen JS, Margolis RL, Albin RL, Miller MI, Ross CA, Wassink T, Cross S, Kimble M, Ryan P, Epping EA, Chiu E, Yastrubetskaya O, Preston J, Goh A, Psych D, Antonopoulos S, Loi S, Chua P, Komiti A, Raymond L, Decolongon J, Varvaris M, Mallonee WM, Suter G, Samii A, Macaraeg A, Jones R, Wood-Siverio C, Factor SA, Testa C, Barker RA, Mason S, McCusker E, Griffith J, Loy C, Gunn D, Orth M, Sübmuth S, Barth K, Trautmann S, Quaid K, Wesson M, Wojcieszek J, Guttman M, Sheinberg A, Karmalkar I, Perlman S, Clemente B, Geschwind MD, Kang G, Satris G, Warner T, Burrows M, Rosser A, Price K, Hunt S, Marshall F, Chesire A, Wodarski M, Hickey C, Panegyres P, Lee J, Andrew S, Perlmutter J, Barton S, Schmidt A, Miedzybrodzka Z, Rae D, D'Alessandro M, Craufurd D, Bek J, Howard E, Mazzoni P, Marder K, Wasserman P, Kumar R, Erickson D, Wheelock V, Tempkin T, Kjer L, Martin W, King P, Wieler M, Sran S, Suchowersk...Danzer P (2014).  Regionally selective atrophy of subcortical structures in prodromal HD as revealed by statistical shape analysis.  Human Brain Mapping.  35(3).  792-809.
  • Staneva V, Younes L (2014).  Modeling and estimation of shape deformation for topology-preserving object tracking.  SIAM Journal on Imaging Sciences.  7(1).  427-455.
  • Afsari B, Fertig EJ, Younes L, Geman D, Marchionni L (2014).  Hardwiring mechanism into predicting cancer phenotypes by computational learning.  Cancer Research.  74(19 Supplement).  5342-5342.
  • Afsari B, Neto UB, Geman D (2014).  Rank Discriminants for Predicting Phenotypes from RNA Expression.  arXiv preprint arXiv:1401.1490.
  • Afsari B, Braga-Neto UM, Geman D (2014).  Rank discriminants for predicting phenotypes from RNA expression.  Annals of Applied Statistics.  8(3).  1469-1491.
  • Tward D, Jovicich J, Soricelli A, Frisoni G, Trouvé A, Younes L, Miller M (2014).  Improved reproducibility of neuroanatomical definitions through diffeomorphometry and complexity reduction.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  8679.  223-230.
  • Sfar AR, Boujemaa N, Geman D (2014).  Confidence Sets for Fine-Grained Categorization and Plant Species Identification.  International Journal of Computer Vision.  1-21.
  • Ardekani S, Gunter G, Jain S, Weiss RG, Miller MI, Younes L (2014).  Estimating dense cardiac 3D motion using sparse 2D tagged MRI cross-sections.  2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014.  5101-5104.
  • Afsari B, Fertig EJ, Geman D, Marchionni L (2014).  switchBox: an R package for k-Top Scoring Pairs classifier development.  Bioinformatics.  btu622.
  • Tang X, Holland D, Dale AM, Younes L, Miller MI (2014).  Shape abnormalities of subcortical and ventricular structures in mild cognitive impairment and Alzheimer's disease: Detecting, quantifying, and predicting.  Human Brain Mapping.  35(8).  3701-3725.
  • Afsari B, Geman D, Fertig EJ (2014).  Learning Dysregulated Pathways in Cancers from Differential Variability Analysis.  Cancer informatics.  13(Suppl 5).  61.
  • Ma S, Sung J, Magis AT, Wang Y, Geman D, Price ND (2014).  Measuring the Effect of Inter-Study Variability on Estimating Prediction Error.  PloS one.  9(10).  e110840.
  • Geman D, Ochs M, Price ND, Tomasetti C, Younes L (2014).  An argument for mechanism-based statistical inference in cancer.  Human genetics.  1-17.
  • Jain S, Tward DJ, Lee DS, Kolasny A, Brown T, Ratnanather JT, Miller MI, Younes L (2014).  Computational anatomy gateway: Leveraging XSEDE computational resources for shape analysis.  ACM International Conference Proceeding Series.
  • Younes L, Albert M, Miller MI (2014).  Inferring changepoint times of medial temporal lobe morphometric change in preclinical Alzheimer's disease.  NeuroImage: Clinical.  5.  178-187.
  • Sfar AR, Boujemaa N, Geman D (2013).  Vantage feature frames for fine-grained categorization.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  835-842.
  • Simcha DM, Younes L, Aryee MJ, Geman D (2013).  Identification of direction in gene networks from expression and methylation..  BMC systems biology.  7.  118.
  • Simcha DM, Younes L, Aryee MJ, Geman D (2013).  Identification of direction in gene networks from expression and methylation.  BMC Systems Biology.  7.
  • Miller MI, Younes L, Ratnanather JT, Brown T, Trinh H, Postell E, Lee DS, Wang MC, Mori S, O'Brien R, Albert M (2013).  The diffeomorphometry of temporal lobe structures in preclinical Alzheimer's disease.  NeuroImage: Clinical.  3.  352-360.
  • Gorospe G, Younes L, Tung L, Vidal R (2013).  A metamorphosis distance for embryonic cardiac action potential interpolation and classification.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  8149 LNCS(PART 1).  469-476.
  • Sung J, Kim PJ, Ma S, Funk CC, Magis AT, Wang Y, Hood L, Geman D, Price ND (2013).  Multi-study Integration of Brain Cancer Transcriptomes Reveals Organ-Level Molecular Signatures.  PLoS Computational Biology.  9(7).
  • Marchionni L, Afsari B, Geman D, Leek JT (2013).  A simple and reproducible breast cancer prognostic test.  BMC Genomics.  14(1).
  • Rejeb Sfar A, Boujemaa N, Geman D (2013).  Identification of plants from multiple images and botanical IdKeys.  ICMR 2013 - Proceedings of the 3rd ACM International Conference on Multimedia Retrieval.  191-198.
  • Tward DJ, Ma J, Miller MI, Younes L (2013).  Robust diffeomorphic mapping via geodesically controlled active shapes.  International Journal of Biomedical Imaging.  2013.
  • Richardson CL, Younes L (2013).  Computing metamorphoses between discrete measures.  Journal of Geometric Mechanics.  5(1).  131-150.
  • Sánchez-Vega F, Younes L, Geman D (2013).  Learning multivariate distributions by competitive assembly of marginals..  IEEE transactions on pattern analysis and machine intelligence.  35(2).  398-410.
  • Jain A, Younes L (2013).  A kernel class allowing for fast computations in shape spaces induced by diffeomorphisms.  Journal of Computational and Applied Mathematics.  245(1).  162-181.
  • Sánchez-Vega F, Eisner J, Younes L, Geman D (2013).  Learning multivariate distributions by competitive assembly of marginals.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  35(2).  398-410.
  • Sung J, Kim P, Ma S, Funk CC, Magis AT, Wang Y, Hood L, Geman D, Price ND (2013).  Multi-study integration of brain cancer transcriptomes reveals organ-level molecular signatures.  PLoS computational biology.  9(7).  e1003148.
  • Marchionni L, Afsari B, Geman D, Leek JT (2013).  A simple and reproducible breast cancer prognostic test.  BMC genomics.  14(1).  336.
  • Vadakkumpadan F, Trayanova N, Younes L, Wu KC (2012).  Left-ventricular shape analysis for predicting sudden cardiac death risk.  Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS.  4067-4070.
  • Simcha D, Price ND, Geman D (2012).  The Limits of De Novo DNA Motif Discovery.  PLoS ONE.  7(11).
  • Winslow RL, Trayanova N, Geman D, Miller MI (2012).  Computational medicine: Translating models to clinical care.  Science Translational Medicine.  4(158).
  • Younes L (2012).  Constrained Diffeomorphic Shape Evolution.  Foundations of Computational Mathematics.  12(3).  295-325.
  • Sánchez-Vega F, Eisner J, Younes E, Geman D (2012).  Learning Multivariate Distributions by Competitive Assembly of Marginals.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  99.
  • Ardekani S, Jain A, Jain S, Abraham TP, Abraham MR, Zimmerman S, Winslow RL, Miller MI, Younes L (2012).  Matching sparse sets of cardiac image cross-sections using large deformation diffeomorphic metric mapping algorithm.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  7085 LNCS.  234-243.
  • Qiu A, Younes L, Miller MI (2012).  Principal component based diffeomorphic surface mapping.  IEEE Transactions on Medical Imaging.  31(2).  302-311.
  • Winslow RL, Trayanova N, Geman D, Miller M (2012).  Computational medicine: translating models to clinical care.  Science translational medicine.  4(158).  158rv11-158rv11.
  • Younes L (2012).  Spaces and manifolds of shapes in computer vision: An overview.  Image and Vision Computing.  30(6-7).  389-397.
  • Simcha D, Price ND, Geman D (2012).  The limits of de novo DNA motif discovery.  PloS one.  7(11).  e47836.
  • Oishi K, Akhter K, Mielke M, Ceritoglu C, Zhang J, Jiang H, Li X, Younes L, Miller MI, van Zijl PCM, Albert M, Lyketsos CG, Mori S (2011).  Multi-modal MRI analysis with disease-specific spatial filtering: Initial testing to predict mild cognitive impairment patients who convert to Alzheimer's disease.  Frontiers in Neurology.  AUG.
  • Reading SAJ, Oishi K, Redgrave GW, Mcentee J, Shanahan M, Yoritomo N, Younes L, Mori S, Miller MI, Van Zijl P, Margolis RL, Ross CA (2011).  Diffuse Abnormality of Low to Moderately Organized White Matter in Schizophrenia.  Brain Connectivity.  1(6).  511-519.
  • Fleuret F, Li T, Dubout C, Wampler EK, Yantis S, Geman D (2011).  Comparing machines and humans on a visual categorization test.  Proceedings of the National Academy of Sciences of the United States of America.  108(43).  17621-17625.
  • Yörük E, Ochs MF, Geman D, Younes L (2011).  A comprehensive statistical model for cell signaling..  IEEE/ACM transactions on computational biology and bioinformatics / IEEE, ACM.  8(3).  592-606.
  • Du J, Younes L, Qiu A (2011).  Whole brain diffeomorphic metric mapping via integration of sulcal and gyral curves, cortical surfaces, and images.  NeuroImage.  56(1).  162-173.
  • Yörük E, Ochs MF, Geman D, Younes L (2011).  A comprehensive statistical model for cell signaling.  IEEE/ACM Transactions on Computational Biology and Bioinformatics.  8(3).  592-606.
  • Slama P, Geman D (2011).  Identification of family-determining residues in PHD fingers.  Nucleic Acids Research.  39(5).  1666-1679.
  • Slama P, Geman D (2011).  Identification of family-determining residues in PHD fingers.  Nucleic acids research.  39(5).  1666-1679.
  • Fleuret F, Li T, Dubout C, Wampler EK, Yantis S, Geman D (2011).  Comparing machines and humans on a visual categorization test.  Proceedings of the National Academy of Sciences.  108(43).  17621-17625.
  • Vidal C, Beggs D, Younes L, Jain SK, Jedynak B (2011).  Incorporating user input in template-based segmentation.  Proceedings - International Symposium on Biomedical Imaging.  1434-1437.
  • Arrate F, Tilak Ratnanather J, Younes L (2010).  Diffeomorphic active contours.  SIAM Journal on Imaging Sciences.  3(2).  176-198.
  • Ma J, Miller MI, Younes L (2010).  A bayesian generative model for surface template estimation.  International Journal of Biomedical Imaging.  2010.
  • Leek JT, Scharpf RB, Bravo HC, Simcha D, Langmead B, Johnson WE, Geman D, Baggerly K, Irizarry RA (2010).  Tackling the widespread and critical impact of batch effects in high-throughput data.  Nature Reviews Genetics.  11(10).  733-739.
  • Eddy JA, Hood L, Price ND, Geman D (2010).  Identifying tightly regulated and variably expressed networks by Differential Rank Conservation (DIRAC).  PLoS Computational Biology.  6(5).  1-17.
  • Allassonnière S, Younes L (2010).  A stochastic algorithm for probabilistic independent component analysis.  Annals of Applied Statistics.  4(1).  125-160.
  • Geman D (2010).  STATISTICAL LEARNING IN COMPUTATIONAL BIOLOGY.  DESCRIPTIFS DES COURS DU M2 MVA MATH EMATIQUES VISION APPRENTISSAGE 2009-2010.
  • Eddy JA, Sung J, Geman D, Price ND (2010).  Relative expression analysis for molecular cancer diagnosis and prognosis.  Technology in cancer research & treatment.  9(2).  149.
  • Leek JT, Scharpf RB, Bravo HC, Simcha D, Langmead B, Johnson W, Geman D, Baggerly K, Irizarry RA (2010).  Tackling the widespread and critical impact of batch effects in high-throughput data.  Nature Reviews Genetics.  11(10).  733-739.
  • Eddy JA, Sung J, Geman D, Price ND (2010).  Relative expression analysis for molecular cancer diagnosis and prognosis.  Technology in Cancer Research and Treatment.  9(2).  149-159.
  • Eddy JA, Hood L, Price ND, Geman D (2010).  Identifying tightly regulated and variably expressed networks by Differential Rank Conservation (DIRAC).  PLoS computational biology.  6(5).  e1000792.
  • Edelman LB, Toia G, Geman D, Zhang W, Price ND (2009).  Two-transcript gene expression classifiers in the diagnosis and prognosis of human diseases.  BMC Genomics.  10.
  • Ardekani S, Weiss RG, Lardo AC, George RT, Lima JAC, Wu KC, Miller MI, Winslow RL, Younes L (2009).  Cardiac motion analysis in ischemic and non-ischemic cardiomyopathy using parallel transport.  Proceedings - 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009.  899-902.
  • Qiu A, Wang L, Younes L, Harms MP, Ratnanather JT, Miller MI, Csernansky JG (2009).  Neuroanatomical asymmetry patterns in individuals with schizophrenia and their non-psychotic siblings.  NeuroImage.  47(4).  1221-1229.
  • Lin X, Afsari B, Marchionni L, Cope L, Parmigiani G, Naiman D, Geman D (2009).  The ordering of expression among a few genes can provide simple cancer biomarkers and signal BRCA1 mutations.  BMC Bioinformatics.  10.  256.
  • Ceritoglu C, Oishi K, Li X, Chou MC, Younes L, Albert M, Lyketsos C, van Zijl PCM, Miller MI, Mori S (2009).  Multi-contrast large deformation diffeomorphic metric mapping for diffusion tensor imaging.  NeuroImage.  47(2).  618-627.
  • Ziane R, Younes L (2009).  Design of a program for straightening standard television pictures taken from the stands. A preliminary stage to the kinematic study of team sport playing actions.  Science et Motricite.  66(1).  71-83.
  • Ardekani S, Weiss RG, Lardo AC, George RT, Lima JAC, Wu KC, Miller MI, Winslow RL, Younes L (2009).  Computational Method for Identifying and Quantifying Shape Features of Human Left Ventricular Remodeling.  Annals of Biomedical Engineering.  37(6).  1043-1054.
  • Chou HF, Younes L (2009).  Smoothing fields of frames using conjugate norms on reproducing kernel hilbert spaces.  Proceedings of SPIE - The International Society for Optical Engineering.  7246.
  • Ferecatu M, Geman D (2009).  A statistical framework for image category search from a mental picture.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  31(6).  1087-1101.
  • Zhang W, Li X, Zhang J, Luft A, Hanley DF, van Zijl P, Miller MI, Younes L, Mori S (2009).  Landmark-referenced voxel-based analysis of diffusion tensor images of the brainstem white matter tracts. Application in patients with middle cerebral artery stroke.  NeuroImage.  44(3).  906-913.
  • Lin X, Afsari B, Marchionni L, Cope L, Parmigiani G, Naiman D, Geman D (2009).  The ordering of expression among a few genes can provide simple cancer biomarkers and signal BRCA1 mutations.  BMC bioinformatics.  10(1).  256.
  • Qiu A, Albert M, Younes L, Miller MI (2009).  Time sequence diffeomorphic metric mapping and parallel transport track time-dependent shape changes..  NeuroImage.  45(1 Suppl).
  • Vidal C, Hewitt J, Davis S, Younes L, Jain S, Jedynak B (2009).  Template registration with missing parts: Application to the segmentation of M. tuberculosis infected lungs.  Proceedings - 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009.  718-721.
  • Holm DD, Trouvé A, Younes L (2009).  The Euler-Poincaré theory of metamorphosis.  Quarterly of Applied Mathematics.  67(4).  661-685.
  • Lin X, Afsari B, Marchionni L, Cope L, Parmigiani G, Naiman D, Geman D (2009).  BMC Bioinformatics.  10.  256.
  • Younes L, Arrate F, Miller MI (2009).  Evolutions equations in computational anatomy..  NeuroImage.  45(1 Suppl).
  • Ferecatu M, Geman D (2009).  A statistical framework for image category search from a mental picture.  Pattern Analysis and Machine Intelligence, IEEE Transactions on.  31(6).  1087-1101.
  • Eddy JA, Geman D, Price ND (2009).  Relative expression analysis for identifying perturbed pathways.  Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009.  5456-5459.
  • Chou HF, Younes L (2009).  Smoothing directional vector fields using dual norms.  SIAM Journal on Imaging Sciences.  2(1).  41-63.
  • Edelman LB, Toia G, Geman D, Zhang W, Price ND (2009).  Two-transcript gene expression classifiers in the diagnosis and prognosis of human diseases.  BMC genomics.  10(1).  583.
  • Eddy JA, Geman D, Price ND (2008).  Pathway expression rank analysis (p-xray): A novel tool for gene set expression analysis.  AIChE Annual Meeting, Conference Proceedings.
  • Geman D, Afsari B, Tan AC, Naiman DQ (2008).  Microarray classification from several twogene expression comparisons.  Proceedings - 7th International Conference on Machine Learning and Applications, ICMLA 2008.  583-585.
  • Glaunès J, Qiu A, Miller MI, Younes L (2008).  Large deformation diffeomorphic metric curve mapping.  International Journal of Computer Vision.  80(3).  317-336.
  • Fleuret F, Geman D (2008).  Stationary features and cat detection.  Journal of Machine Learning Research.  9.  2549-2578.
  • Wang JZ, Geman D, Luo J, Gray RM (2008).  Real-world image annotation and retrieval: An introduction to the special section.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  30(11).  1873-1876.
  • Younes L, Qiu A, Winslow RL, Miller MI (2008).  Transport of relational structures in groups of diffeomorphisms.  Journal of Mathematical Imaging and Vision.  32(1).  41-56.
  • Ma J, Miller MI, Trouvé A, Younes L (2008).  Bayesian template estimation in computational anatomy.  NeuroImage.  42(1).  252-261.
  • Qiu A, Younes L, Miller MI, Csernansky JG (2008).  Parallel transport in diffeomorphisms distinguishes the time-dependent pattern of hippocampal surface deformation due to healthy aging and the dementia of the Alzheimer's type.  NeuroImage.  40(1).  68-76.
  • Xu L, Tan AC, Winslow RL, Geman D (2008).  Merging microarray data from separate breast cancer studies provides a robust prognostic test.  BMC Bioinformatics.  9.
  • Qiu A, Younes L, Miller MI (2008).  Intrinsic and extrinsic analysis in computational anatomy.  NeuroImage.  39(4).  1803-1814.
  • Huang H, Yamamoto A, Hossain MA, Younes L, Mori S (2008).  Quantitative cortical mapping of fractional anisotropy in developing rat brains.  Journal of Neuroscience.  28(6).  1427-1433.
  • Wang J, Geman D, Luo J, Gray R (2008).  SPECIAL SECTION ON REAL-WORLD IMAGE ANNOTATION AND RETRIEVAL-Real-World Image Annotation and Retrieval: An Introduction to the Special Section.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  30(11).  1873.
  • Eddy JA, Geman D, Price ND (2008).  Pathway Expression Rank Analysis (p-XRAY): A Novel Tool for Gene Set Expression Analysis.  The 2008 Annual Meeting.
  • Xu L, Tan AC, Winslow RL, Geman D (2008).  Merging microarray data from separate breast cancer studies provides a robust prognostic test.  Bmc Bioinformatics.  9(1).  125.
  • Fleuret F, Geman D (2008).  Stationary features and cat detection.  Journal of Machine Learning Research.  9(2549-2578).  16.
  • Younes L, Michor PW, Shah J, Mumford D (2008).  A metric on shape space with explicit geodesics.  Atti della Accademia Nazionale dei Lincei, Classe di Scienze Fisiche, Matematiche e Naturali, Rendiconti Lincei Matematica e Applicazioni.  19(1).  25-57.
  • Wang JZ, Geman D, Luo J, Gray RM (2008).  Real-world image annotation and retrieval: an introduction to the special section.  Pattern Analysis and Machine Intelligence, IEEE Transactions on.  30(11).  1873-1876.
  • Sirong Z, Younes L, Zweck J, Ratnanather JT (2007).  Diffeomorphic surface flows: A novel method of surface evolution.  SIAM Journal on Applied Mathematics.  68(3).  806-824.
  • Ferecatu M, Geman D (2007).  Interactive search for image categories by mental matching.  Proceedings of the IEEE International Conference on Computer Vision.
  • Beg MF, Dickie R, Golds G, Younes L (2007).  Consistent realignment of 3D diffusion tensor MRI eigenvectors.  Progress in Biomedical Optics and Imaging - Proceedings of SPIE.  6512(PART 3).
  • Qiu A, Younes L, Wang L, Ratnanather JT, Gillepsie SK, Kaplan G, Csernansky J, Miller MI (2007).  Combining anatomical manifold information via diffeomorphic metric mappings for studying cortical thinning of the cingulate gyrus in schizophrenia.  NeuroImage.  37(3).  821-833.
  • Xu L, Geman D, Winslow RL (2007).  Large-scale integration of cancer microarray data identifies a robust common cancer signature.  BMC Bioinformatics.  8.
  • Anderson TJ, Tchernyshyov I, Diez R, Cole RN, Geman D, Dang CV, Winslow RL (2007).  Discovering robust protein biomarkers for disease from relative expression reversals in 2-D DIGE data.  Proteomics.  7(8).  1197-1207.
  • Wang L, Beg F, Ratnanather T, Ceritpglu C, Younes L, Morris JC, Csernansky JG, Miller MI (2007).  Large deformation diffeomorphism and momentum based hippocampal shape discrimination in dementia of the alzheimer type.  IEEE Transactions on Medical Imaging.  26(4).  462-470.
  • Gadat S, Younes L (2007).  A stochastic algorithm for feature selection in pattern recognition.  Journal of Machine Learning Research.  8.  509-547.
  • Anderson TJ, Tchernyshyov I, Diez R, Cole RN, Geman D, Dang CV, Winslow RL (2007).  Discovering robust protein biomarkers for disease from relative expression reversals in 2-D DIGE data..  Proteomics.  7(8).  1197-1207.
  • Younes L (2007).  Jacobi fields in groups of diffeomorphisms and applications.  Quarterly of Applied Mathematics.  65(1).  113-134.
  • Xu L, Geman D, Winslow RL (2007).  Large-scale integration of cancer microarray data identifies a robust common cancer signature.  BMC bioinformatics.  8(1).  275.
  • Gangaputra S, Geman D (2006).  A design principle for coarse-to-fine classification.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  2.  1877-1884.
  • Cao Y, Miller MI, Mori S, Winslow RL, Younes L (2006).  Diffeomorphic matching of diffusion tensor images.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  2006.
  • Geman D (2006).  Interactive image retrieval by mental matching.  Proceedings of the ACM International Multimedia Conference and Exhibition.  1-2.
  • Wang JZ, Boujemaa N, Del Bimbo A, Geman D, Hauptmann AG, Tešic J (2006).  Diversity in multimedia information retrieval research.  Proceedings of the ACM International Multimedia Conference and Exhibition.  5-12.
  • Garcin L, Younes L (2006).  Geodesic matching with free extremities.  Journal of Mathematical Imaging and Vision.  25(3).  329-340.
  • Sahbi H, Geman D (2006).  A hierarchy of support vector machines for pattern detection.  Journal of Machine Learning Research.  7.  2087-2123.
  • Younes L (2006).  Combining geodesic interpolating splines and affine transformations.  IEEE Transactions on Image Processing.  15(5).  1111-1119.
  • Feldman T, Younes L (2006).  Homeostatic image perception: An artificial system.  Computer Vision and Image Understanding.  102(1).  70-80.
  • Miller MI, Trouvé A, Younes L (2006).  Geodesic shooting for computational anatomy.  Journal of Mathematical Imaging and Vision.  24(2).  209-228.
  • Sahbi H, Geman D (2006).  A hierarchy of support vector machines for pattern detection.  The Journal of Machine Learning Research.  7.  2087-2123.
  • Helm PA, Younes L, Beg MF, Ennis DB, Leclercq C, Faris OP, McVeigh E, Kass D, Miller MI, Winslow RL (2006).  Evidence of structural remodeling in the dyssynchronous failing heart.  Circulation Research.  98(1).  125-132.
  • Trouvé A, Younes L (2005).  Local geometry of deformable templates.  SIAM Journal on Mathematical Analysis.  37(1).  17-59.
  • Garcin L, Younes L (2005).  Geodesic image matching: A wavelet based energy minimization scheme.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  3757 LNCS.  349-364.
  • Cao Y, Miller MI, Winslow RL, Younes L (2005).  Large deformation diffeomorphic metric mapping of fiber orientations.  Proceedings of the IEEE International Conference on Computer Vision.  II.  1379-1386.
  • Allassonnière S, Trouvé A, Younes L (2005).  Geodesic shooting and diffeomorphic matching via textured meshes.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  3757 LNCS.  365-381.
  • Fang Y, Geman D (2005).  Experiments in mental face retrieval.  Lecture Notes in Computer Science.  3546.  637-646.
  • Tan AC, Naiman DQ, Xu L, Winslow RL, Geman D (2005).  Simple decision rules for classifying human cancers from gene expression profiles.  Bioinformatics.  21(20).  3896-3904.
  • Xu L, Tan AC, Naiman DQ, Geman D, Winslow RL (2005).  Robust prostate cancer marker genes emerge from direct integration of inter-study microarray data.  Bioinformatics.  21(20).  3905-3911.
  • Helm PA, Tseng HJ, Younes L, McVeigh ER, Winslow RL (2005).  Ex vivo 3D diffusion tensor imaging and quantification of cardiac laminar structure.  Magnetic Resonance in Medicine.  54(4).  850-859.
  • Cao Y, Miller MI, Winslow RL, Younes L (2005).  Large deformation diffeomorphic metric mapping of vector fields.  IEEE Transactions on Medical Imaging.  24(9).  1216-1230.
  • Blanchard G, Geman D (2005).  Hierarchical testing designs for pattern recognition.  Annals of Statistics.  33(3).  1155-1202.
  • Bitouk D, Miller MI, Younes L (2005).  Clutter invariant ATR.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  27(5).  817-821.
  • Trouvé A, Younes L (2005).  Metamorphoses through lie group action.  Foundations of Computational Mathematics.  5(2).  173-198.
  • Beg MF, Miller MI, Trouvé A, Younes L (2005).  Computing large deformation metric mappings via geodesic flows of diffeomorphisms.  International Journal of Computer Vision.  61(2).  139-157.
  • Koloydenko A, Geman D (2005).  Ordinal coding of image microstructure.  Eurandom.
  • Blanchard G, Geman D (2005).  Hierarchical testing designs for pattern recognition.  Annals of Statistics.  1155-1202.
  • Geman D, Koloydenko A (2005).  Spatial Adaptation in Coding Microstructure of Natural Images..
  • Xu L, Tan AC, Naiman D, Geman D, Winslow RL (2005).  Robust prostate cancer marker genes emerge from direct integration of inter-study microarray data.  Bioinformatics.  21(20).  3905-3911.
  • Tan AC, Naiman D, Xu L, Winslow RL, Geman D (2005).  Simple decision rules for classifying human cancers from gene expression profiles.  Bioinformatics.  21(20).  3896-3904.
  • Blanchard G, Geman D (2005).  EPrint Removed.  Annals of Statistics.  33(3).  1155-1202.
  • Fang Y, Geman D, Boujemaa N (2005).  An interactive system for mental face retrieval.  MIR 2005 - Proceedings of the 7th ACM SIGMM International Workshop on Multimedia Information Retrieval, Co-located with ACM Multimedia 2005.  193-200.
  • Gangaputra S, Geman D (2005).  A unified stochastic model for detecting and tracking faces.  Proceedings - 2nd Canadian Conference on Computer and Robot Vision, CRV 2005.  306-313.
  • Lu L, Hager GD, Younes L (2005).  A three tiered approach for articulated object action modeling and recognition.  Advances in Neural Information Processing Systems.
  • Fan X, Geman D (2004).  Hierarchical object indexing and sequential learning.  Proceedings - International Conference on Pattern Recognition.  3.  65-68.
  • Guo H, Rangarajan A, Joshi S, Younes L (2004).  Non-rigid registration of shapes via diffeomorphic point matching.  2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano.  1.  924-927.
  • Garcin L, Rangarajan A, Younes L (2004).  Non rigid registration of shapes via diffeomorphic point matching and clustering.  Proceedings - International Conference on Image Processing, ICIP.  2.  3299-3302.
  • Geman D, D'Avignon C, Naiman DQ, Winslow RL (2004).  Classifying gene expression profiles from pairwise mRNA comparisons.  Statistical Applications in Genetics and Molecular Biology.  3(1).
  • Amit Y, Geman D, Fan X (2004).  A coarse-to-fine strategy for multiclass shape detection.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  26(12).  1606-1621.
  • Vaillant M, Miller MI, Younes L, Trouvé A (2004).  Statistics on diffeomorphisms via tangent space representations.  NeuroImage.  23(SUPPL. 1).
  • Holm DD, Tilak Ratnanather J, Trouvé A, Younes L (2004).  Soliton dynamics in computational anatomy.  NeuroImage.  23(SUPPL. 1).
  • Gangaputra S, Geman D (2004).  Self-normalized linear tests.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  2.
  • Glaunes J, Trouvé A, Younes L (2004).  Diffeomorphic matching of distributions: A new approach for unlabelled point-sets and sub-manifolds matching.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  2.
  • D'Avignon C, Geman D (2004).  Tree-structured neural decoding.  Journal of Machine Learning Research.  4(4).  743-754.
  • Amit Y, Geman D, Fan X (2004).  A coarse-to-fine strategy for multiclass shape detection.  Pattern Analysis and Machine Intelligence, IEEE Transactions on.  26(12).  1606-1621.
  • Guo H, Rangarajan A, Joshi SC, Younes L (2004).  A new joint clustering and diffeomorphism estimation algorithm for non-rigid shape matching.  IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops.  2004-January(January).
  • Geman D, d’Avignon C, Naiman D, Winslow RL (2004).  Classifying gene expression profiles from pairwise mRNA comparisons.  Statistical applications in genetics and molecular biology.  3(1).
  • Geman D, d’Avignon C, Naiman D, Winslow R, Zeboulon A (2004).  Gene expression comparisons for class prediction in cancer studies.  Proceedings 36'th Symposium on the Interface: Computing Science and Statistics.
  • Geman D (2004).  Study around path classification in a ternary tree.
  • Miller MI, Trouvé A, Younes L (2003).  The metric spaces, Euler equations, and normal geodesic image motions of computational anatomy.  IEEE International Conference on Image Processing.  2.  635-638.
  • Bitouk D, Miller MI, Younes L (2003).  Asymptotic Performance Analysis for Object Recognition in Clutter.  Proceedings of SPIE - The International Society for Optical Engineering.  5094.  101-108.
  • Beg MF, Miller M, Trouvé A, Younes L (2003).  The Euler-Lagrange equation for interpolating sequence of landmark datasets.  Lecture Notes in Computer Science.  2879(PART 2).  918-925.
  • Geman D (2003).  Mathematical Sciences 550: 437 Information, Statistics and Perception.
  • d’Avignon C, Geman D (2003).  Tree-structured neural decoding.  The Journal of Machine Learning Research.  4.  743-754.
  • Beg MF, Miller MI, Trouve A, Younes L (2002).  Computing metrics on anatomical shapes in computational anatomy.  Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings.  2.  989-990.
  • Bitouk D, Miller MI, Younes L (2002).  Empirically generated metric spaces for ATR in clutter.  Conference Record of the Asilomar Conference on Signals, Systems and Computers.  2.  1407-1410.
  • Fleuret F, Geman D (2002).  Fast face detection with precise pose estimation.  Proceedings - International Conference on Pattern Recognition.  16(1).  235-238.
  • Miller MI, Trouvé A, Younes L (2002).  On the metrics and Euler-Lagrange equations of computational anatomy.  Annual Review of Biomedical Engineering.  4.  375-405.
  • Sahbi H, Geman D, Boujemaa N (2002).  Face detection using coarse-to-fine support vector classifiers.  IEEE International Conference on Image Processing.  3.
  • Beg MF, Miller MI, Trouvé A, Younes L (2002).  Computational anatomy: Computing metrics on anatomical shapes.  Proceedings - International Symposium on Biomedical Imaging.  2002-January.  341-344.
  • Geman D, Jedynak B (2001).  Model-based classification trees.  IEEE Transactions on Information Theory.  47(3).  1075-1082.
  • Fleuret F, Geman D (2001).  Coarse-to-fine face detection.  International Journal of Computer Vision.  41(1-2).  85-107.
  • Fleuret F, Geman D (2001).  Coarse-to-fine face detection.  International Journal of computer vision.  41(1-2).  85-107.
  • Camion V, Younes L (2001).  Geodesic interpolating splines.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  2134.  523-527.
  • Miller MI, Younes L (2001).  Group actions, homeomorphisms, and matching: A general framework.  International Journal of Computer Vision.  41(1-2).  61-84.
  • Geman D, Jedynak B (2001).  Model-based classification trees.  IEEE Transactions on Information Theory.  47(3).  1075-1082.
  • Trouvé A, Younes L (2000).  On a class of diffeomorphic matching problems in one dimension.  SIAM Journal on Control and Optimization.  39(4).  1112-1135.
  • Bereziat D, Herlin I, Younes L (2000).  Generalized optical flow constraint and its physical interpretation.  Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.  2.  487-492.
  • Younes L (2000).  Calibrating parameters of cost functionals.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  1843.  212-223.
  • Geman D, Moquet R (2000).  A stochastic feedback model for image retrieval.  Proc. RFIA.  3.  173-180.
  • Geman D, Moquet R (2000).  Q & a models for interactive search.  Preprint, December.
  • cois Fleuret F, Geman D (2000).  Coarse-to-Fine Face Detection.  Citeseer.
  • Trouvé A, Younes L (2000).  Diffeomorphic matching problems in one dimension: Designing and minimizing matching functionals.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  1842.  573-587.
  • Amit Y, Geman D (1999).  A Computational Model for Visual Selection.  Neural Computation.  11(7).  1691-1715.
  • Fleuret F, Geman D (1999).  Coarse-to-fine visual selection.  Citeseer.
  • Younes L (1999).  Optimal matching between shapes via elastic deformations.  Image and Vision Computing.  17(5).  381-389.
  • cois Fleuret F, Geman D (1999).  Coarse-to-Fine Visual Selection.  Citeseer.
  • Amit Y, Geman D (1999).  A computational model for visual selection.  Neural computation.  11(7).  1691-1715.
  • Fleuret F, Geman D (1999).  Graded learning for object detection.  Proc. IEEE Workshop Statistical and Computational Theories of Vision.  544-549.
  • cois Fleuret F, Geman D (1999).  Graded Learning for Object Detection.  Citeseer.
  • Geman D (1999).  Statistical Learning and Coarse-to-fine Object Detection.  COMPUTING SCIENCE AND STATISTICS.  60-60.
  • Geman D, Koloydenko A (1999).  Invariant statistics and coding of natural microimages.  IEEE Workshop on Statistical and Computational Theories of Vision.
  • Bereziat D, Herlin I, Younes L (1999).  Motion estimation using a volume conservation hypothesis.  ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings.  6.  3385-3388.
  • Younes L (1998).  Stochastic gradient estimation strategies for Markov random fields.  Proceedings of SPIE - The International Society for Optical Engineering.  3459.  315-325.
  • Younes L (1998).  Synchronous random fields and image restoration.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  20(4).  380-390.
  • Amit Y, Geman D (1998).  Discussion: Arcing Classifiers.  Annals of Statistics.  833-837.
  • Younes L (1998).  Computable elastic distances between shapes.  SIAM Journal on Applied Mathematics.  58(2).  565-586.
  • Amit Y, Geman D, Wilder K (1997).  Joint induction of shape features and tree classifiers.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  19(11).  1300-1305.
  • Béréziat D, Herlin I, Younes L (1997).  Motion detection in meteorological images sequences: Two methods and their comparison.  Proceedings of SPIE - The International Society for Optical Engineering.  3217.  332-341.
  • Azencott R, Wang JP, Younes L (1997).  Texture classification using windowed fourier filters.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  19(2).  149-152.
  • Amit Y, Geman D (1997).  Shape Quantization and Recognition with Randomized Trees.  Neural Computation.  9(7).  1545-1588.
  • Azencott R, Wang JP, Younes L (1997).  Texture classification using windowed Fourier filters.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  19(2).  148-153.
  • Amit Y, Geman D (1997).  Shape quantization and recognition with randomized trees.  Neural computation.  9(7).  1545-1588.
  • Amit Y, Geman D, Wilder K (1997).  Joint induction of shape features and tree classifiers.  Pattern Analysis and Machine Intelligence, IEEE Transactions on.  19(11).  1300-1305.
  • Amit Y, Geman D, Wilder K (1997).  Joint induction of shape features and tree classifiers.  Citeseer.
  • Azencott R, Younes L (1997).  An energy minimization method for matching and comparing structured object representations.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  1223.  441-456.
  • Geman D, Jedynak B (1996).  An active testing model for tracking roads in satellite images.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  18(1).  1-14.
  • Geman D, Jedynak B (1996).  An active testing model for tracking roads in satellite images.  Pattern Analysis and Machine Intelligence, IEEE Transactions on.  18(1).  1-14.
  • Azencott R, Coldefy F, Younes L (1996).  A distance for elastic matching in object recognition.  Proceedings - International Conference on Pattern Recognition.  1.  687-691.
  • Younes L (1996).  Synchronous Boltzmann machines can be universal approximators.  Applied Mathematics Letters.  9(3).  109-113.
  • Geman D (1996).  Wiley & Sons, 1989. 1181 C. Goad," Special purpose automatic programming for three-dimensional model-based vision," Proc. ARPA Image Understand-ing Workshop, pp. 94-104, 1983. 1191 C. Graffigne and I. Herlin," Mod6lisation de reseaux pour.  IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE.  18(1).
  • Geman D, Yang C (1995).  Nonlinear image recovery with half-quadratic regularization.  Image Processing, IEEE Transactions on.  4(7).  932-946.
  • Geman D, Yang C (1995).  Nonlinear Image Recovery with Half-Quadratic Regularization.  IEEE Transactions on Image Processing.  4(7).  932-946.
  • Younes L (1994).  Synchronous image restoration.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  801 LNCS.  213-217.
  • Geman D, Horowitz J (1993).  Searching for circumstellar disks with space telescope observations.  Proceedings of the 1993 IEEE International Symposium on Information Theory.  133.
  • Geman D, Jedynak B, others (1993).  Shape recognition and twenty questions.
  • Geman D, Geman S (1993).  Stochastic relaxation, Gibbs distributions and the Bayesian restoration of images*.  Journal of Applied Statistics.  20(5-6).  25-62.
  • Azencott R, Doutriaux A, Younes L (1993).  Synchronous boltzmann machines and curve identification tasks.  Network: Computation in Neural Systems.  4(4).  461-480.
  • Geman S, McClure DE, Geman D (1992).  A nonlinear filter for film restoration and other problems in image processing.  CVGIP: Graphical Models and Image Processing.  54(4).  281-289.
  • Geman D, Geman S, McClure DE (1992).  A nonlinear filter for film restoration and other problems in image processing.  CVGIP: Graphical models and image processing.  54(4).  281-289.
  • Geman D, Reynolds G (1992).  Constrained Restoration and the Recovery of Discontinuities.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  14(3).  367-383.
  • Geman D, Reynolds G (1992).  Constrained restoration and the recovery of discontinuities.  IEEE Transactions on pattern analysis and machine intelligence.  14(3).  367-383.
  • Geman D, GEMAN S (1992).  Reprinted with permission from IEEE Transactions on Pattern Analysis and Machine Intelligence. Vol. PAMI-6 (6), pp. 721-741 (November 1984). 1984 IEEE..  Selected papers on digital image restoration.  47.  263.
  • Geman D, Gidas B (1991).  Image analysis and computer vision.  Spatial statistics and digital image analysis.  9-36.
  • Geman D, Grenander U, Piccioni M, Presutti E (1990).  Fees and registration.  Signal Processing.  20.  189-191.
  • Dong P, Geman D, Geman S, Graffigne C (1990).  Boundary detection by constrained optimization.  Pattern Analysis and Machine Intelligence, IEEE Transactions on.  12(7).  609-628.
  • Geman D, Geman S, Graffigne C, Dong P (1990).  Boundary Detection by Constrained Optimization.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  12(7).  609-628.
  • Younes L (1989).  Parametric Inference for imperfectly observed Gibbsian fields.  Probability Theory and Related Fields.  82(4).  625-645.
  • Branch B, Geman D (1988).  The Valuation of Stochastic Cash Flows.  Quarterly Journal of Business and Economics.  148-178.
  • Geman D (1987).  Stochastic model for boundary detection.  Image and Vision Computing.  5(2).  61-65.
  • Geman D (1987).  Stochastic model for boundary detection.  Image and Vision Computing.  5(2).  61-65.
  • Geman D (1985).  BAYESIAN IMAGE ANALYSIS BY ADAPTIVE ANNEALING..  Digest - International Geoscience and Remote Sensing Symposium (IGARSS).  269-276.
  • Geman D (1985).  Bayesian image analysis by adaptive annealing.  IEEE Transactions on Geoscience and Remote Sensing.  1.  269-276.
  • Geman D, Geman S (1984).  Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images.  Pattern Analysis and Machine Intelligence, IEEE Transactions on.  (6).  721-741.
  • Geman D, Horowitz J, Rosen J (1984).  A local time analysis of intersections of Brownian paths in the plane.  The Annals of Probability.  86-107.
  • Cristi R, Derin H, Elliott H, Geman D (1984).  Bayes smoothing algorithms for segmentation of binary images modeled by Markov random fields.  Pattern Analysis and Machine Intelligence, IEEE Transactions on.  (6).  707-720.
  • Geman S, Geman D (1984).  Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  PAMI-6(6).  721-741.
  • Derin H, Elliott H, Cristi R, Geman D (1984).  BAYES SMOOTHING ALGORITHMS FOR SEGMENTATION OF IMAGES MODELED BY MARKOV RANDOM FIELDS..  ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings.  2.
  • Derin H, Elliott H, Cristi R, Geman D (1984).  Bayes Smoothing Algorithms for Segmentation of Binary Images Modeled by Markov Random Fields.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  PAMI-6(6).  707-720.
  • Elliott H, Derin H, Cristi R, Geman D (1984).  APPLICATION OF THE GIBBS DISTRIBUTION TO IMAGE SEGMENTATION..  ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings.  2.
  • Lakhoua R, Dougui N, Zemmi F, Dhaqui F, Younes L, Jedidi H (1982).  Juvenile diabetes.  Tunisie Medicale.  60(4).  113-127.
  • Geman D, Horowitz J, Karatzas I, Mason DM, Rosen J, Stout QF, Warren B, Yamato H (1982).  THE ANNALS.  The Annals of Statistics.  10(2).
  • Geman D, Horowitz J (1981).  Smooth perturbations of a function with a smooth local time.  Transactions of the American Mathematical Society.  267(2).  517-530.
  • Geman D, Horowitz J (1981).  Smooth perturbations of a function with a smooth local time.  Transactions of the American Mathematical Society.  267(2).  517-530.
  • Geman D, Horowitz J (1980).  Occupation densities.  The Annals of Probability.  1-67.
  • Geman D (1980).  Confluent Brownian Motions.  Advances in Applied Probability.  306-306.
  • Densities O, Diaconis P, Freedman D, Geman D, Ghoussoub N, Horowitz J, Metivier M, others , Pellaumail J, Philipp W, Steele JM (1980).  Special Invited Paper.
  • Geman D, HOROWITZ J (1980).  SPECIAL INVITED PAPER.  The Annals of Probability.  8(1).  1-67.
  • Geman D (1979).  Dispersion points for linear sets and approximate moduli for some stochastic processes.  Transactions of the American Mathematical Society.  253.  257-272.
  • Geman D (1979).  Dispersion points for linear sets and approximate moduli for some stochastic processes.  Transactions of the American Mathematical Society.  253.  257-272.
  • Geman D, Zinn J (1978).  On the increments of multidimensional random fields.  The Annals of Probability.  151-158.
  • Cuzick J, Davisson L, Geman D, Hosoya Y, Ledrappier F, Neuhoff D, Portnoy S, Shields P, Steele JM, Zinn J (1978).  VOLUME 6 February 1978 No..  THE ANNALS OF PROBABILITY.  6(1).
  • Geman D (1977).  On the approximate local growth of multidimensional random fields.  Zeitschrift für Wahrscheinlichkeitstheorie und Verwandte Gebiete.  38(3).  237-251.
  • Geman D (1977).  On the approximate local growth of multidimensional random fields.  Probability Theory and Related Fields.  38(3).  237-251.
  • Geman D, Horowitz J (1976).  Occupation-times for functions with countable level sets and the regeneration of stationary processes.  Zeitschrift für Wahrscheinlichkeitstheorie und Verwandte Gebiete.  35(3).  189-211.
  • Geman D, Horowitz J (1976).  Local times for real and random functions.  Duke Mathematical Journal.  43(4).  809-828.
  • Geman D, Horowitz J (1976).  Local times for real and random functions.  Duke Mathematical Journal.  43(4).  809-828.
  • Geman D (1976).  A note on the continuity of local times1.  Proceedings of the American Mathematical Society.  57(2).  321-326.
  • Geman D (1976).  A note on the continuity of local times.  Proceedings of the American Mathematical Society.  321-326.
  • Geman D, Horowitz J (1976).  Occupation-times for functions with countable level sets and the regeneration of stationary processes.  Probability Theory and Related Fields.  35(3).  189-211.
  • Geman D, Horowitz J, Zinn J (1976).  Recurrence of stationary sequences.  The Annals of Probability.  372-381.
  • Geman D, Gianini J, Horowitz J, Hwang J, Mitt-vl Y, Samuels SM, Tomkins IJ, Ylvisaker D, Zinn J (1976).  THE ANNALS.  The Annals of Probability.  4(3).
  • Geman D, Horowitz J (1975).  Random shifts which preserve measure.  Proceedings of the American Mathematical Society.  49(1).  143-150.
  • Geman D, Horowitz J (1975).  Polar sets and Palm measures in the theory of flows.  Transactions of the American Mathematical Society.  208.  141-159.
  • Geman D, Horowitz J (1975).  Polar sets and palm measures in the theory of flows.  Transactions of the American Mathematical Society.  208.  141-159.
  • Geman D, Horowitz J (1975).  RANDOM SHIFTS WHICH PRESERVE MEASURE1.  AMERICAN MATHEMATICAL SOCIETY.  49(1).
  • Geman D, Horowitz J (1974).  Local times and supermartingales.  Zeitschrift für Wahrscheinlichkeitstheorie und Verwandte Gebiete.  29(4).  273-293.
  • Geman D, Horowitz J (1974).  Local times and supermartingales.  Probability Theory and Related Fields.  29(4).  273-293.
  • Geman D, Horowitz J (1974).  Transformations of flows by discrete random measures.  INDIANA UNIVERSITY MATHEMATICS JOURNAL.  24(4).  291-306.
  • Geman D, Horowitz J (1974).  TRANSFORMATIONS OF FLOWS BY DISCRETE RANDOM MEASURES..  Indiana University Mathematics Journal.  24(4).  291-306.
  • Geman D (1973).  A note on the distribution of hitting times.  The Annals of Probability.  1(5).  854-856.
  • Geman D, Horowitz J (1973).  Occupation times for smooth stationary processes.  The Annals of Probability.  1(1).  131-137.
  • Geman D, Horowitz J (1973).  Remarks on Palm measures.  Annales de l’institut Henri Poincaré (B) Probabilités et Statistiques.  9(3).  215-232.
  • Geman D, Horowitz J (1973).  Remarks on Palm measures.  Annales de l’institut Henri Poincaré (B) Probabilités et Statistiques.  9(3).  215-232.
  • Geman D (1972).  On the variance of the number of zeros of a stationary Gaussian process.  The Annals of Mathematical Statistics.  977-982.
Books
  • Ancona A, Geman D, Ikeda N (1991).  École d'été de probabilités de Saint-Flour XVIII-1988.  Springer.  18.
  • Ancona A, Geman D, Hennequin PL, Ikeda N (1990).  Probabilites.  Springer-Verlag.
  • Geman D, Geman SA (1987).  Relaxation and annealing with constraints.  Center for Intelligent Control Systems.
Book Chapters
  • Younes L (2019).  Diffeomorphic Matching.  Applied Mathematical Sciences (Switzerland).  171.  291-346.
  • Younes L (2019).  Deformable Templates.  Applied Mathematical Sciences (Switzerland).  171.  169-181.
  • Younes L (2019).  Metamorphosis.  Applied Mathematical Sciences (Switzerland).  171.  373-404.
  • Younes L (2019).  Computations on Triangulated Surfaces.  Applied Mathematical Sciences (Switzerland).  171.  101-130.
  • Younes L (2019).  Ordinary Differential Equations and Groups of Diffeomorphisms.  Applied Mathematical Sciences (Switzerland).  171.  183-203.
  • Younes L (2019).  Evolving Curves and Surfaces.  Applied Mathematical Sciences (Switzerland).  171.  131-167.
  • Younes L (2019).  Building Admissible Spaces.  Applied Mathematical Sciences (Switzerland).  171.  205-241.
  • Younes L (2019).  Local Properties of Surfaces.  Applied Mathematical Sciences (Switzerland).  171.  73-100.
  • Younes L (2019).  Parametrized Plane Curves.  Applied Mathematical Sciences (Switzerland).  171.  1-55.
  • Younes L (2019).  Shapes and diffeomorphisms.  Applied Mathematical Sciences (Switzerland).  171.  1-316.
  • Younes L (2019).  Analyzing Shape Datasets.  Applied Mathematical Sciences (Switzerland).  171.  405-421.
  • Younes L (2019).  Distances and Group Actions.  Applied Mathematical Sciences (Switzerland).  171.  347-372.
  • Bauer M, Charon N, Younes L (2019).  Metric registration of curves and surfaces using optimal control.  Handbook of Numerical Analysis.  20.  613-646.
  • Younes L (2019).  Deformable Objects and Matching Functionals.  Applied Mathematical Sciences (Switzerland).  171.  243-289.
  • Younes L (2019).  The Medial Axis.  Applied Mathematical Sciences (Switzerland).  171.  57-72.
  • Trouvé A, Younes L (2015).  Shape spaces.  Handbook of Mathematical Methods in Imaging: Volume 1, Second Edition.  1759-1817.
  • Younes L (2010).  Diffeomorphic Matching.  Applied Mathematical Sciences (Switzerland).  171.  249-301.
  • Younes L (2010).  Building Admissible Spaces.  Applied Mathematical Sciences (Switzerland).  171.  177-202.
  • Younes L (2010).  Ordinary Differential Equations and Groups of Diffeomorphisms.  Applied Mathematical Sciences (Switzerland).  171.  161-176.
  • Younes L (2010).  Isocontours and Isosurfaces.  Applied Mathematical Sciences (Switzerland).  171.  105-113.
  • Younes L (2010).  Evolving Curves and Surfaces.  Applied Mathematical Sciences (Switzerland).  171.  115-148.
  • Younes L (2010).  Distances and Group Actions.  Applied Mathematical Sciences (Switzerland).  171.  303-329.
  • Younes L (2010).  Deformable Objects and Matching Functionals.  Applied Mathematical Sciences (Switzerland).  171.  203-247.
  • Younes L (2010).  Deformable templates.  Applied Mathematical Sciences (Switzerland).  171.  149-160.
  • Younes L (2010).  Medial Axis.  Applied Mathematical Sciences (Switzerland).  171.  43-57.
  • Younes L (2010).  Local Properties of Surfaces.  Applied Mathematical Sciences (Switzerland).  171.  65-103.
  • Younes L (2010).  Parametrized Plane Curves.  Applied Mathematical Sciences (Switzerland).  171.  1-42.
  • Younes L (2010).  Moment-Based Representation.  Applied Mathematical Sciences (Switzerland).  171.  59-63.
  • Younes L (2010).  Metamorphosis.  Applied Mathematical Sciences (Switzerland).  171.  331-345.
  • Glaunès J, Trouvé A, Younes L (2006).  Modeling Planar Shape Variation via Hamiltonian flows of curves.  Modeling and Simulation in Science, Engineering and Technology.  (9780817643768).  335-361.
  • Gangaputra S, Geman D (2006).  The trace model for object detection and tracking.  Toward Category-Level Object Recognition.  Springer.  401-420.
  • Fang Y, Geman D (2005).  Experiments in mental face retrieval.  Audio-and Video-Based Biometric Person Authentication.  Springer.  637-646.
  • Geman D (2003).  Coarse-to-fine classification and scene labeling.  Nonlinear Estimation and Classification.  Springer New York.  31-48.
  • Amit Y, Geman D, Jedynak B (1998).  Efficient focusing and face detection.  Face Recognition.  Springer Berlin Heidelberg.  157-173.
  • Geman D, Jedynak B, Jung F (1997).  Recognizing buildings in aerial images.  Automatic Extraction of Man-Made Objects from Aerial and Space Images (II).  Birkhäuser Basel.  173-182.
  • Geman D, Horowitz J, Kepner J (1994).  Computation of IRAS Fluxes via a Priori Astrometry.  Infrared Astronomy with Arrays.  Springer.  179-180.
  • Geman D (1990).  Random fields and inverse problems in imaging.  École d’été de probabilités de Saint-Flour XVIII-1988.  Springer Berlin Heidelberg.  113-193.
  • Geman D, Geman S, Graffigne C (1987).  Locating texture and object boundaries.  Pattern Recognition Theory and Applications.  Springer.  165-177.
  • Geman D, Geman S (1986).  Bayesian image analysis.  Disordered Systems and Biological Organization.  Springer.  301-319.
Other Publications
  • Amit Y, Geman D, Fan X (2003).  Computational strategies for model-based scene interpretation.  Technical report, The Johns Hopkins University, 2003. http://www. cis. jhu. edu/ xdfan/strategies. pdf.
  • Krempp S, Geman D, Amit Y (2002).  Sequential learning of reusable parts for object detection.  Technical report, CS Johns Hopkins.
  • Amit Y, Geman D (1994).  Randomized Inquiries About Shape: An Application to Handwritten Digit Recognition..  DTIC Document.
  • Geman D, Geman S, Gidas B, Grenander U, McClure DE (1991).  A Mathematical Framework for Image Analysis.  DTIC Document.
  • Bienenstock E, Geman D, Geman S, McClure DE (1990).  Development of Laser Radar ATR Algorithms: Phase 2. Military Objects.  DTIC Document.
  • Geman D, Geman S, Grenander U, McClure DE (1987).  Image Modeling: A Mathematical Framework for Segmentation and Object Detection..  DTIC Document.
  • Geman D, Geman S, Grenander U, McClure DE (1987).  A Unified Mathematical Approach to Image Analysis..  DTIC Document.
  • Cristi R, Derin H, Elliott H, Geman D (1983).  Application of the Gibbs Distribution to Image Segmentation..  MASSACHUSETTS UNIV AMHERST DEPT OF ELECTRICAL AND COMPUTER ENGINEERING.
  • Cristi R, Derin H, Elliott H, Geman D (1983).  Bayes Smoothing Algorithms for Segmentation of Images Modelled by Markov Random Fields..  DTIC Document.
  • Geman D (1977).  Singularities in the Distribution of the Increments of a Smooth Function..  DTIC Document.
Conference Proceedings
  • Sfar AR, Boujemaa N, Geman D (2013).  Vantage Feature Frames For Fine-Grained Categorization.  Computer Vision and Pattern Recognition (CVPR), 2013 IEEE Conference on.  835-842.
  • Rejeb Sfar A, Boujemaa N, Geman D (2013).  Identification of plants from multiple images and botanical idkeys.  Proceedings of the 3rd ACM conference on International conference on multimedia retrieval.  191-198.
  • Eddy JA, Geman D, Price ND (2009).  Relative expression analysis for identifying perturbed pathways.  Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE.  5456-5459.
  • Ferecatu M, Geman D (2007).  Interactive search for image categories by mental matching.  Computer Vision, 2007. ICCV 2007. IEEE 11th International Conference on.  1-8.
  • Gangaputra S, Geman D (2006).  A design principle for coarse-to-fine classification.  Computer Vision and Pattern Recognition, 2006 IEEE Computer Society Conference on.  1877-1884.
  • Geman D (2006).  In Search of a Unifying Theory for Image Interpretation.  Information Theory, 2006 IEEE International Symposium on.  xliv-xliv.
  • Geman D (2006).  Interactive image retrieval by mental matching.  Proceedings of the 8th ACM international workshop on Multimedia information retrieval.  1-2.
  • Wang JZ, Boujemaa N, Del Bimbo A, Geman D, Hauptmann AG, Tesic J (2006).  Diversity in multimedia information retrieval research.  Proceedings of the 8th ACM international workshop on Multimedia information retrieval.  5-12.
  • Gangaputra S, Geman D (2005).  A unified stochastic model for detecting and tracking faces.  Computer and Robot Vision, 2005. Proceedings. The 2nd Canadian Conference on.  306-313.
  • Fang Y, Geman D, Boujemaa N (2005).  An interactive system for mental face retrieval.  Proceedings of the 7th ACM SIGMM international workshop on Multimedia information retrieval.  193-200.
  • Gangputra S, Geman D (2004).  Self-normalized linear tests.  Computer Vision and Pattern Recognition, 2004. CVPR 2004. Proceedings of the 2004 IEEE Computer Society Conference on.  II-616.
  • Fan X, Geman D (2004).  Hierarchical object indexing and sequential learning.  Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on.  65-68.
  • Sahbi H, Geman D, Boujemaa N (2002).  Face detection using coarse-to-fine support vector classifiers.  Image Processing. 2002. Proceedings. 2002 International Conference on.  925-928.
  • Fleuret F, Geman D (2002).  Fast face detection with precise pose estimation.  Pattern Recognition, 2002. Proceedings. 16th International Conference on.  235-238.
  • Geman D (1994).  The entropy strategy for shape recognition.  Information Theory and Statistics, 1994. Proceedings., 1994 IEEE-IMS Workshop on.  8.
  • Geman D, Horowitz J (1993).  Searching for Circumstellar Disks with Space Telescope Observations.  Information Theory, 1993. Proceedings. 1993 IEEE International Symposium on.  133-133.
  • Geman D (1991).  Remarks on Hard Modeling vs. Image Processing, Circumstellar Disks and Model Validation.  The Restoration of HST Images and Spectra.  74.
  • Geman D, Jedynak B (1991).  Detection of roads in satellite images.  Geoscience and Remote Sensing Symposium, 1991. IGARSS'91. Remote Sensing: Global Monitoring for Earth Management., International.  2473-2477.
  • Geman D, GEMAN S, GRENANDER U, MCCLURE D (1984).  THE PARALLEL REALIZATION OF MARKOV RANDOM-FIELDS WITH APPLICATIONS TO PROBLEMS IN INFERENCE AND OPTIMIZATION.  STOCHASTIC PROCESSES AND THEIR APPLICATIONS.  (1).  34-35.
  • Geman D, HOROWITZ J (1971).  PALM PROBABILITIES AND ADDITIVE FUNCTIONALS. 1. PRELIMINARY REPORT.  NOTICES OF THE AMERICAN MATHEMATICAL SOCIETY.  (6).  972.
  • Geman D (1971).  VARIANCE OF NUMBER OF ZEROS OF A STATIONARY GAUSSIAN PROCESS.  ANNALS OF MATHEMATICAL STATISTICS.  (5).  1794.
  • "A visual Turing test for computer vision systems", ONR Workshop.  Durham, North Carolina.  October 25, 2015
Back to top