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The Journal of Chemical Physics|October 2, 2020
Molecular force fields with gradient-domain machine learning (GDML): Comparison and synergies with classical force fieldsHuziel E Sauceda, Michael Gastegger, Stefan Chmiela, et al.The Journal of Physical Chemistry Letters|December 13, 2021
Significance of the Chemical Environment of an Element in Nonadiabatic Molecular Dynamics: Feature Selection and Dimensionality Reduction with Machine LearningWei Bin How, Bipeng Wang, Weibin Chu, et al.Chemical Science|September 16, 2024
SpaiNN: equivariant message passing for excited-state nonadiabatic molecular dynamicsSascha Mausenberger, Carolin Müller, Alexandre Tkatchenko, et al.Science Advances|November 9, 2019
Impact of nuclear vibrations on van der Waals and Casimir interactions at zero and finite temperaturePrashanth S Venkataram, Jan Hermann, Teerit J Vongkovit, et al.The Journal of Chemical Physics|September 6, 2020
Improved description of ligand polarization enhances transferability of ion-ligand interactionsVered Wineman-Fisher, Yasmine Al-Hamdani, Péter R Nagy, et al.Chemical Research in Toxicology|September 10, 2023
Equivariant Graph Neural Networks for Toxicity PredictionJulian Cremer, Leonardo Medrano Sandonas, Alexandre Tkatchenko, et al.The Journal of Physical Chemistry Letters|February 16, 2019
Nonadditivity of the Adsorption Energies of Linear Acenes on Au(111): Molecular Anisotropy and Many-Body EffectsFriedrich Maass, Mohsen Ajdari, Fairoja Cheenicode Kabeer, et al.Nature Communications|January 20, 2021
Dynamical strengthening of covalent and non-covalent molecular interactions by nuclear quantum effects at finite temperatureHuziel E Sauceda, Valentin Vassilev-Galindo, Stefan Chmiela, et al.Proceedings of the National Academy of Sciences of the United States of America|February 13, 2018
Fast and accurate quantum Monte Carlo for molecular crystalsAndrea Zen, Jan Gerit Brandenburg, Jiří Klimeš, et al.Journal of Cheminformatics|February 27, 2025
Pretraining graph transformers with atom-in-a-molecule quantum properties for improved ADMET modelingAlessio Fallani, Ramil Nugmanov, Jose Arjona-Medina, et al.Pageof 21