Showing 1–20 of 21 results
/ Date/ Name
Jul 23, 2024The need to implement FAIR principles in biomolecular simulationsSep 11, 2023Reaction coordinate flows for model reduction of molecular kineticsJul 26, 2023DeepQMC: an open-source software suite for variational optimization of deep-learning molecular wave functionsFeb 14, 2023Statistically Optimal Force Aggregation for Coarse-Graining Molecular DynamicsMar 17, 2022Electronic excited states in deep variational Monte CarloOct 1, 2021Smooth Normalizing FlowsAug 3, 2021Temperature Steerable Flows and Boltzmann GeneratorsJun 14, 2021Machine Learning Implicit Solvation for Molecular DynamicsJun 3, 2020Equivariant Flows: Exact Likelihood Generative Learning for Symmetric DensitiesFeb 16, 2020Stochastic Normalizing FlowsNov 2, 2019Special Topic: Markov Models of Molecular KineticsSep 16, 2019Deep neural network solution of the electronic Schrödinger equationDec 18, 2018Machine Learning for Molecular Dynamics on Long TimescalesDec 4, 2018Machine Learning of coarse-grained Molecular Dynamics Force FieldsNov 28, 2018Variational Selection of Features for Molecular KineticsApr 20, 2018Grand canonical diffusion-influenced reactions: a stochastic theory with applications to multiscale reaction-diffusion simulationsDec 21, 2017MSM/RD: Coupling Markov state models of molecular kinetics with reaction-diffusion simulationsOct 30, 2017Time-lagged autoencoders: Deep learning of slow collective variables for molecular kineticsMar 4, 2016Reversible Markov chain estimation using convex-concave programmingSep 12, 2013Projected and Hidden Markov Models for calculating kinetics and metastable states of complex molecules