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| 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 |
