13 citations · 26 across the 3 of their papers we have counts for
3 papers
Enhancing Protein-Ligand Binding Affinity Predictions using Neural Network Potentials
Francesc Sabanes Zariquiey, Raimondas Galvelis, Emilio Gallicchio +3
This letter gives results on improving protein-ligand binding affinity predictions based on molecular dynamics simulations using machine learning potentials with a hybrid neural ne…
Spatial Attention Kinetic Networks with E(n)-Equivariance
Yuanqing Wang, John D. Chodera
Neural networks that are equivariant to rotations, translations, reflections, and permutations on n-dimensional geometric space have shown promise in physical modeling for tasks su…
SPICE, A Dataset of Drug-like Molecules and Peptides for Training Machine Learning Potentials
Peter Eastman, Pavan Kumar Behara, David L. Dotson +9
Machine learning potentials are an important tool for molecular simulation, but their development is held back by a shortage of high quality datasets to train them on. We describe…