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Jonathan Vandermause — most-cited papers & profile · AI for Science
← authors
·
overview
Jonathan Vandermause
8
papers ·
48
citations
Google Scholar ↗
Semantic Scholar ↗
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Most-cited papers
Micron-scale heterogeneous catalysis with Bayesian force fields from first principles and active learning
2022 · 24 citations
Accurate and scalable multi-element graph neural network force field and molecular dynamics with direct force architecture
2020 · 16 citations
Unraveling the Catalytic Effect of Hydrogen Adsorption on Pt Nanoparticle Shape-Change
2023 · 4 citations
Active learning of reactive Bayesian force fields: Application to heterogeneous hydrogen-platinum catalysis dynamics
2021 · 2 citations
Uncertainty-aware molecular dynamics from Bayesian active learning for Phase Transformations and Thermal Transport in SiC
2022 · 1 citations
Phase discovery with active learning: Application to structural phase transitions in equiatomic NiTi
2024 · 1 citations
Multitask machine learning of collective variables for enhanced sampling of rare events
2020
Uncertainty Driven Active Learning of Coarse Grained Free Energy Models
2022
Top co-authors
Boris Kozinsky
· 8
Anders Johansson
· 3
Cameron J. Owen
· 3
Yu Xie
· 3
Lixin Sun
· 2
Yu Xie
· 2
Anatoly I. Frenkel
· 1
Blake R. Duschatko
· 1
Cheol Woo Park
· 1
Chris Wolverton
· 1
David Clark
· 1
Jin Soo Lim
· 1
Topics
Chemistry
Materials
Physics ML
Protein Science