Physics ∩ ML
a virtual hub at the interface of theoretical physics and deep learning.
Past talks:
06
Apr 2022
Formal Mathematics Statement Curriculum Learning
Stanislas Polu, OpenAI
30
Mar 2022
Machine Learning Statistical Gravity from Multi-Region Entanglement Entropy
Yi-Zhuang You, UCSD
23
Mar 2022
Tuning Large Neural Networks via Zero-Shot Hyperparameter Transfer
Greg Yang, Microsoft Research
16
Mar 2022
BI for AI: Energy conserving descent for optimization
Eva Silverstein, Stanford
16
Feb 2022
Fast and Credible Inference with Truncated Marginal Neural Ratio Estimation
Alex Cole, University of Amsterdam
02
Feb 2022
Equivariant Neural Fields: A Roadmap Towards Generalizable Neural Representation and Inference
Ge Yang, IAIFI and MIT
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