Physics ∩ ML
a virtual hub at the interface of theoretical physics and deep learning.
The Importance of Being Interpretable
Michelle Ntampaka, Space Telescope Science Institute, 12:00 EDT
Ben Wandelt, Flatiron Institute, 12:00 EDT
Quantum Machine Learning in High Energy Physics
Sofia Vallecorsa, CERN, 12:00 EDT
Two talks from string_data 2020
Haggai Maron (NVIDIA Research) and Sergei Gukov (CalTech), 12:00 EDT
Feature Learning in Infinite-Width Neural Networks
Greg Yang, Microsoft Research, 12:00 EDT
Harnessing Data Revolution in Quantum Matter
Eun-Ah Kim, Cornell University, 12:00 EDT
Euclidean Neural Networks: Adventures in learning with 3D geometry and geometric tensors.
Tess Smidt, Lawrence Berkeley Laboratory, 12:00 EDT
Flow-based likelihoods for non-Gaussian inference.
Ana Diaz Rivero, Harvard University, 12:00 EDT
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