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DTSTART;TZID=America/New_York:20231109T110000
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DTSTAMP:20260404T002225
CREATED:20230829T201346Z
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UID:9545-1699527600-1699531200@seasevents.nmsdev7.com
SUMMARY:ESE Fall Seminar - "Approximate symmetries in machine learning"
DESCRIPTION:In this talk\, we explain different roles that symmetries and approximate symmetries can play in machine learning models. We define approximately equivariant graph neural networks and we show a bias-variance tradeoff when selecting the symmetries to enforce. We explain how to see equivariant functions as gradients of invariant functions\, and we show how to use these ideas in self-supervised learning.
URL:https://seasevents.nmsdev7.com/event/ese-fall-seminar-title-tbd-7/
LOCATION:Glandt Forum\, Singh Center for Nanotechnology\, 3205 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Colloquium
ORGANIZER;CN="Electrical and Systems Engineering":MAILTO:eseevents@seas.upenn.edu
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