{"id":30541,"date":"2021-06-16T09:10:48","date_gmt":"2021-06-16T13:10:48","guid":{"rendered":"https:\/\/engineering.jhu.edu\/ams\/event\/ams-seminar-tom-needham-florida-state-university-whitehead-304\/"},"modified":"2021-12-30T08:50:14","modified_gmt":"2021-12-30T13:50:14","slug":"ams-seminar-tom-needham-florida-state-university-whitehead-304","status":"publish","type":"tribe_events","link":"https:\/\/engineering.jhu.edu\/ams\/event\/ams-seminar-tom-needham-florida-state-university-whitehead-304\/","title":{"rendered":"AMS Seminar: Tom Needham (Florida State University) @ Whitehead 304"},"content":{"rendered":"<p>Title:\u00a0 Optimal Transport-Based Distances for Metric Space Matching<br \/>Abstract: I will overview some methods for comparing datasets modeled as metric measure spaces (mm-spaces), which are compact metric spaces endowed with probability measures. The main tool is Gromov-Wasserstein (GW) distance, which provides a metric on the collection of all mm-spaces. The definition of GW distance is inspired by ideas from optimal transport and it has fascinating connections to many other areas of mathematics. I will discuss theoretical results on estimating GW distance using distribution-valued invariants of mm-spaces as well as some work on the use of GW distance for practical applications in data science.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Title:\u00a0 Optimal Transport-Based Distances for Metric Space MatchingAbstract: I will overview some methods for comparing datasets modeled as metric measure spaces (mm-spaces), which are compact metric spaces endowed with probability&hellip;<\/p>\n","protected":false},"author":3,"featured_media":0,"template":"","meta":{"_acf_changed":false,"_relevanssi_hide_post":"","_relevanssi_hide_content":"","_relevanssi_pin_for_all":"","_relevanssi_pin_keywords":"","_relevanssi_unpin_keywords":"","_relevanssi_related_keywords":"","_relevanssi_related_include_ids":"","_relevanssi_related_exclude_ids":"","_relevanssi_related_no_append":"","_relevanssi_related_not_related":"","_relevanssi_related_posts":"","_relevanssi_noindex_reason":"","_tribe_events_status":"","_tribe_events_status_reason":"","footnotes":""},"tags":[],"tribe_events_cat":[],"class_list":["post-30541","tribe_events","type-tribe_events","status-publish","hentry"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.7 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>AMS Seminar: Tom Needham (Florida State University) @ Whitehead 304 | Department of Applied Mathematics and Statistics<\/title>\n<meta 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