Physics ∩ ML
a virtual hub at the interface of theoretical physics and deep learning.
To be determined.
Lenka Zdeborova, Université Paris-Saclay, 12:00 EDT
The large learning rate phase of deep learning
Yasaman Bahri, Google Brain, 12:00 EDT
Discovering new phases of matter with unsupervised and interpretable support vector machines
Lode Pollet, LMU Munich, 12:00 EDT
Discovering Symbolic Models in Physical Systems using Deep Learning
Shirley Ho, Flatiron Institute, 12:00 EDT
String data and machine learning
Andre Lukas, University of Oxford, 12:00 EDT
Learning for Safety-Critical Control in Dynamical Systems
Yisong Yue, CalTech, 12:00 EDT
Deep Learning and Quantum Gravity
Koji Hashimoto, Osaka University, 12:00 EDT
Why do neural networks generalise in the overparameterised regime?
Ard Louis, University of Oxford, 12:00 EDT
Building symmetries into generative flow models
Phiala Shanahan, MIT, 12:00 EDT
Natural Graph Networks
Taco Cohen, Qualcomm AI Research, 12:00 EDT
About Physics ∩ ML