molecular dynamics

PathFlow: A normalizing flow generator that finds transition paths UAI 2022 Bayesian Quadrature on Riemannian Data Manifolds ICML 2021 Deep Molecular Representation Learning via Fusing Physical and Chemical Information NeurIPS 2021 GemNet: Universal Directional Graph Neural Networks for Molecules NeurIPS 2021 Smooth Normalizing Flows NeurIPS 2021 Deep Statistical Solvers NeurIPS 2020 Equivariant Flows: Exact Likelihood Generative Learning for Symmetric Densities ICML 2020 JAX MD: A Framework for Differentiable Physics NeurIPS 2020 Statistical Estimation of the Poincaré constant and Application to Sampling Multimodal Distributions AISTATS 2020 Deep Generative Markov State Models NeurIPS 2018 SchNet: A continuous-filter convolutional neural network for modeling quantum interactions NeurIPS 2017 Understanding Protein Dynamics with L1-Regularized Reversible Hidden Markov Models ICML 2014