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02/14/2023
Statistically Optimal Force Aggregation for Coarse-Graining Molecular Dynamics
Machine-learned coarse-grained (CG) models have the potential for simula...
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02/01/2023
Two for One: Diffusion Models and Force Fields for Coarse-Grained Molecular Dynamics
Coarse-grained (CG) molecular dynamics enables the study of biological p...
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12/14/2022
Machine Learning Coarse-Grained Potentials of Protein Thermodynamics
A generalized understanding of protein dynamics is an unsolved scientifi...
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06/14/2021
Machine Learning Implicit Solvation for Molecular Dynamics
Accurate modeling of the solvent environment for biological molecules is...
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12/22/2020
TorchMD: A deep learning framework for molecular simulations
Molecular dynamics simulations provide a mechanistic description of mole...
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07/22/2020
Coarse Graining Molecular Dynamics with Graph Neural Networks
Coarse graining enables the investigation of molecular dynamics for larg...
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05/04/2020
Ensemble Learning of Coarse-Grained Molecular Dynamics Force Fields with a Kernel Approach
Gradient-domain machine learning (GDML) is an accurate and efficient app...
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11/22/2019
Machine learning for protein folding and dynamics
Many aspects of the study of protein folding and dynamics have been affe...
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11/07/2019
Machine learning for molecular simulation
Machine learning (ML) is transforming all areas of science. The complex ...
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09/23/2019
Data-driven approximation of the Koopman generator: Model reduction, system identification, and control
We derive a data-driven method for the approximation of the Koopman gene...
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08/12/2019
Tensor-based EDMD for the Koopman analysis of high-dimensional systems
Recent years have seen rapid advances in the data-driven analysis of dyn...
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12/04/2018
Machine Learning of coarse-grained Molecular Dynamics Force Fields
Atomistic or ab-initio molecular dynamics simulations are widely used to...
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12/06/2017
