Upcoming talks:
Past talks:
Learning Differential Equations
Jesse Bettencourt, University of Toronto, 12:00 ETExplaining Neural Scaling Laws
Ethan Dyer, Google, 12:00 ETDeep 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 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.