1 citations · 2 across the 2 of their papers we have counts for
2 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}…