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Joint Theory Seminar: Jack Collins

Description Speaker: Jack Collins
Title: Representation Learning for Collider Events
Host: Da Liu
Zoom: https://zoom.us/j/186024391

Abstract:
Collider events, when imbued with a metric which characterizes the 'distance' between two events, can be thought of as populating a data manifold in a metric space. The geometric properties of this manifold reflect the physics encoded in the distance metric. I will show how the geometry of collider events can be probed using a class of machine learning architectures called Variational Autoencoders.
Date Mon, May 11, 2020
Time 1:30pm-2:30pm PDT
Duration 1 hour
Access Public
Created by High-Energy Seminars
Updated Sat, May 2, 2020 3:41pm PDT
Send Reminder Yes  -  0 days 4 hour 0 minutes before start

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