BEGIN:VCALENDAR VERSION:2.0 PRODID:-//Drupal iCal API//EN X-WR-CALNAME:Events items teaser X-WR-TIMEZONE:America/Toronto BEGIN:VTIMEZONE TZID:America/Toronto X-LIC-LOCATION:America/Toronto BEGIN:DAYLIGHT TZNAME:EDT TZOFFSETFROM:-0500 TZOFFSETTO:-0400 DTSTART:20220313T070000 END:DAYLIGHT BEGIN:STANDARD TZNAME:EST TZOFFSETFROM:-0400 TZOFFSETTO:-0500 DTSTART:20211107T060000 END:STANDARD END:VTIMEZONE BEGIN:VEVENT UID:683373af86845 DTSTART;TZID=America/Toronto:20220624T130000 SEQUENCE:0 TRANSP:TRANSPARENT DTEND;TZID=America/Toronto:20220624T140000 URL:/computer-science/events/phd-seminar-machine-learni ng-out-of-distribution-detection-with-flow-generative-models SUMMARY:PhD Seminar • Machine Learning • Out-of-distribution Detection\ nwith Flow Generative Models CLASS:PUBLIC DESCRIPTION:Summary \n\nPLEASE NOTE: THIS PHD SEMINAR WILL BE GIVEN ONLINE. \n\nDIHONG JIANG\, PHD CANDIDATE\n_David R. Cheriton School of Computer Sc ience_\n\nSUPERVISOR: Professor Yaoliang Yu\n\nOut-of-distribution (OOD) d ata come from a distribution that is\ndifferent from training data. Detect ing OOD data contributes to secure\ndeployment of machine learning models. Currently\, deep generative\nmodels have been widely used as an unsupervi sed approach for OOD\ndetection.\n DTSTAMP:20250525T194655Z END:VEVENT END:VCALENDAR