1 citations · 1 across the 2 of their papers we have counts for
3 papers
Autodifferentiable Geometric Restraints for Enhanced Sampling Simulations with Classical and Machine Learned Force Fields
Gustavo R. Pérez-Lemus, Cintia A. Menendez, Yinan Xu +3
The use of external restraints is ubiquitous in advanced molecular simulation techniques. In general, restraints serve to reduce the configurational space that is available for sam…
The Importance of Learning without Constraints: Reevaluating Benchmarks for Invariant and Equivariant Features of Machine Learning Potentials in Generating Free Energy Landscapes
Gustavo R. Pérez-Lemus, Yinan Xu, Yezhi Jin +2
Machine-learned interatomic potentials (MILPs) are rapidly gaining interest for molecular modeling, as they provide a balance between quantum-mechanical level descriptions of atomi…
PySAGES: flexible, advanced sampling methods accelerated with GPUs
Pablo F. Zubieta Rico, Ludwig Schneider, Gustavo R. Pérez-Lemus +11
Molecular simulations are an important tool for research in physics, chemistry, and biology. The capabilities of simulations can be greatly expanded by providing access to advanced…