Physics ∩ ML

a virtual hub at the interface of theoretical physics and deep learning.

Upcoming talks:

21 Apr 2021

Machine Learning for Calabi-Yau metrics

Fabian Ruehle, CERN and Oxford, 12:00 ET
05 May 2021

TBA

Kyle Cranmer, NYU, 12:00 ET

Past talks:

07 Apr 2021
24 Mar 2021

Algebraic Neural Networks

Alejandro Ribeiro, University of Pennsylvania, 12:00 ET
10 Mar 2021

Generative and Invertible Networks for the LHC

Tilman Plehn, Heidelberg University, 12:00 EDT
24 Feb 2021
10 Feb 2021

Physics 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 EDT
27 Jan 2021

The 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.