1 citations · 2 across the 3 of their papers we have counts for
3 papers
physics.chem-ph2023★ 1 cited
Beyond potential energy surface benchmarking: a complete application of machine learning to chemical reactivity
Xingyi Guan, Joseph Heindel, Taehee Ko +2
We train an equivariant machine learning model to predict energies and forces for a real-world study of hydrogen combustion under conditions of finite temperature and pressure. Thi…
physics.chem-ph2023★ 1 cited
Using Diffusion Maps to Analyze Reaction Dynamics for a Hydrogen Combustion Benchmark Dataset
Taehee Ko, Joseph Heindel, Xingyi Guan +3
We use local diffusion maps to assess the quality of two types of collective variables (CVs) for a recently published hydrogen combustion benchmark dataset~\cite{guan2022benchmark}…
cs.LG2020
HydroNet: Benchmark Tasks for Preserving Intermolecular Interactions and Structural Motifs in Predictive and Generative Models for Molecular Data
Sutanay Choudhury, Jenna A. Bilbrey, Logan Ward +5
Intermolecular and long-range interactions are central to phenomena as diverse as gene regulation, topological states of quantum materials, electrolyte transport in batteries, and…