activity
20202022
most citedCombining Machine Learning and Computational Chemistry for Predictive Insights Into Chemical Systems

876 citations · 1k across the 6 of their papers we have counts for

collaborators

6 papers

physics.chem-ph2022★ 9 cited

Accurate global machine learning force fields for molecules with hundreds of atoms

Stefan Chmiela, Valentin Vassilev-Galindo, Oliver T. Unke +4

Global machine learning force fields (MLFFs), that have the capacity to capture collective many-atom interactions in molecular systems, currently only scale up to a few dozen atoms…

physics.chem-ph2022★ 41 cited

Towards Linearly Scaling and Chemically Accurate Global Machine Learning Force Fields for Large Molecules

Adil Kabylda, Valentin Vassilev-Galindo, Stefan Chmiela +2

Machine learning force fields (MLFFs) are gradually evolving towards enabling molecular dynamics simulations of molecules and materials with ab initio accuracy but at a small fract…

physics.chem-ph2021

Improving Molecular Force Fields Across Configurational Space by Combining Supervised and Unsupervised Machine Learning

Gregory Fonseca, Igor Poltavsky, Valentin Vassilev-Galindo +1

The training set of atomic configurations is key to the performance of any Machine Learning Force Field (MLFF) and, as such, the training set selection determines the applicability…

physics.chem-ph2021★ 52 cited

Challenges for Machine Learning Force Fields in Reproducing Potential Energy Surfaces of Flexible Molecules

Valentin Vassilev-Galindo, Gregory Fonseca, Igor Poltavsky +1

Dynamics of flexible molecules are often determined by an interplay between local chemical bond fluctuations and conformational changes driven by long-range electrostatics and van…

physics.chem-ph2021★ 876 cited

Combining Machine Learning and Computational Chemistry for Predictive Insights Into Chemical Systems

John A. Keith, Valentin Vassilev-Galindo, Bingqing Cheng +4

Machine learning models are poised to make a transformative impact on chemical sciences by dramatically accelerating computational algorithms and amplifying insights available from…

physics.chem-ph2020★ 51 cited

Dynamical Strengthening of Covalent and Non-Covalent Molecular Interactions by Nuclear Quantum Effects at Finite Temperature

Huziel E. Sauceda, Valentin Vassilev-Galindo, Stefan Chmiela +2

Nuclear quantum effects (NQE) tend to generate delocalized molecular dynamics due to the inclusion of the zero point energy and its coupling with the anharmonicities in interatomic…