Upcoming talks:
Past talks:
Deep Neural Networks for Ab Initio Quantum Chemistry
David Pfau, Deepmind, 12:00 ETAre wider nets better given the same number of parameters?
Anna Golubeva, Perimeter Institute, 12:00 ETExplorations at the Physics ∩ ML Interface
Kyle Cranmer, NYU, 12:00 ETMachine Learning for Calabi-Yau metrics
Fabian Ruehle, CERN and Oxford, 12:00 ETA 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 ET
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.