74 citations · 100 across the 4 of their papers we have counts for
Showing 2020Show all
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physics.comp-ph2020★ 5 cited
Temperature-steerable flows
Manuel Dibak, Leon Klein, Frank Noé
Boltzmann generators approach the sampling problem in many-body physics by combining a normalizing flow and a statistical reweighting method to generate samples of a physical syste…
cs.LG2020
Relevance of Rotationally Equivariant Convolutions for Predicting Molecular Properties
Benjamin Kurt Miller, Mario Geiger, Tess E. Smidt +1
Equivariant neural networks (ENNs) are graph neural networks embedded in and are well suited for predicting molecular properties. The ENN library e3nn has customizab…
stat.ML2020
Stochastic Normalizing Flows
Hao Wu, Jonas Köhler, Frank Noé
The sampling of probability distributions specified up to a normalization constant is an important problem in both machine learning and statistical mechanics. While classical stoch…