198 citations · 351 across the 8 of their papers we have counts for
8 papers
Enhanced Diffusion Sampling: Efficient Rare Event Sampling and Free Energy Calculation with Diffusion Models
Yu Xie, Ludwig Winkler, Lixin Sun +10
The rare-event sampling problem has long been the central limiting factor in molecular dynamics (MD), especially in biomolecular simulation. Recently, diffusion models such as BioE…
Operator Forces For Coarse-Grained Molecular Dynamics
Leon Klein, Atharva Kelkar, Aleksander Durumeric +2
Coarse-grained (CG) molecular dynamics simulations extend the length and time scale of atomistic simulations by replacing groups of correlated atoms with CG beads. Machine-learned…
Learning data efficient coarse-grained molecular dynamics from forces and noise
Aleksander E. P. Durumeric, Yaoyi Chen, Frank Noé +1
Machine-learned coarse-grained (MLCG) molecular dynamics is a promising option for modeling biomolecules. However, MLCG models currently require large amounts of data from referenc…
Navigating protein landscapes with a machine-learned transferable coarse-grained model
Nicholas E. Charron, Felix Musil, Andrea Guljas +18
The most popular and universally predictive protein simulation models employ all-atom molecular dynamics (MD), but they come at extreme computational cost. The development of a uni…
Statistically Optimal Force Aggregation for Coarse-Graining Molecular Dynamics
Andreas Krämer, Aleksander P. Durumeric, Nicholas E. Charron +3
Machine-learned coarse-grained (CG) models have the potential for simulating large molecular complexes beyond what is possible with atomistic molecular dynamics. However, training…
Flow-matching -- efficient coarse-graining of molecular dynamics without forces
Jonas Köhler, Yaoyi Chen, Andreas Krämer +2
Coarse-grained (CG) molecular simulations have become a standard tool to study molecular processes on time- and length-scales inaccessible to all-atom simulations. Parameterizing C…
Machine Learning Implicit Solvation for Molecular Dynamics
Yaoyi Chen, Andreas Krämer, Nicholas E. Charron +3
Accurate modeling of the solvent environment for biological molecules is crucial for computational biology and drug design. A popular approach to achieve long simulation time scale…
Coarse Graining Molecular Dynamics with Graph Neural Networks
Brooke E. Husic, Nicholas E. Charron, Dominik Lemm +9
Coarse graining enables the investigation of molecular dynamics for larger systems and at longer timescales than is possible at atomic resolution. However, a coarse graining model…