Upcoming talks:
TBA
Kyle Cranmer, NYU, 12:00 ETPast talks:
A Mathematical Exploration of Why Language Models Help Solve Downstream Tasks
Nikunj Saunshi, Princeton University, 12:00 EDTAlgebraic Neural Networks
Alejandro Ribeiro, University of Pennsylvania, 12:00 ETGenerative and Invertible Networks for the LHC
Tilman Plehn, Heidelberg University, 12:00 EDTNeural Mechanics: Symmetry and Broken Conservation Laws in Deep Learning Dynamics
Daniel Kunin and Hidenori Tanaka, 12:00 EDTPhysics meets ML to solve cosmological inference
Ben Wandelt, Institut d’Astrophysique de Paris / Institut Lagrange, Sorbonne University and Center for Computational Astrophysics, Flatiron Institute, New York, 12:00 EDTThe Importance of Being Interpretable
Michelle Ntampaka, Space Telescope Science Institute, 12:00 EDT
For link and password to the talks, please
sign up for the Physics ∩ ML mailing list.
Videos may be found on our YouTube channel and slides by clicking on past talk titles.
Videos may be found on our YouTube channel and slides by clicking on past talk titles.