134 citations · 437 across the 17 of their papers we have counts for
3 papers · 1 filter
ML Models of Vibrating HCO: Comparing Reproducing Kernels, FCHL and PhysNet
Silvan Käser, Debasish Koner, Anders S. Christensen +2
Machine Learning (ML) has become a promising tool for improving the quality of atomistic simulations. Using formaldehyde as a benchmark system for intramolecular interactions, a co…
Machine Learning for Observables: Reactant to Product State Distributions for Atom-Diatom Collisions
Julian Arnold, Debasish Koner, Silvan Käser +3
Machine learning-based models to predict product state distributions from a distribution of reactant conditions for atom-diatom collisions are presented and quantitatively tested.…
Isomerization and Decomposition Reactions of Acetaldehyde Relevant to Atmospheric Processes from Dynamics Simulations on Neural Network-Based Potential Energy Surfaces
Silvan Käser, Oliver T. Unke, Markus Meuwly
Acetaldehyde (AA) isomerization (to vinylalcohol, VA) and decomposition (into either CO+CH and H+HCCO) is studied using a fully dimensional, reactive potential energy s…