Predictive collective variable discovery with deep Bayesian models for atomistic systems.
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Updated
Oct 23, 2020 - Python
Predictive collective variable discovery with deep Bayesian models for atomistic systems.
Generate coarse-grained molecular dynamics models from atomistic trajectories.
Tools to build coarse grained models and perform simulations with OpenMM
Thesis repository on neural ordinary differential equations used for coarse-graining molecular dynamics
[TMLR 2023] Simulate time-integrated coarse-grained MD with multi-scale graph neural networks
COSMO: COarse-grained Simulation of intrinsically disordered prOteins with openMM
End-To-End Molecular Dynamics (MD) Engine using PyTorch
A general cross-platform tool for preparing simulations of molecules and complex molecular assemblies
COBY (Coarse Grained System Builder) can be used to create coarse-grained systems in Martini 3
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