Machine learning in chemical reaction space

por Sina Stocker, Gábor Csányi, Karsten Reuter, Johannes T. Margraf
Publicado 2020

A general-purpose machine-learning force field for bulk and nanostructured phosphorus

por Volker L. Deringer, Miguel A. Caro, Gábor Csányi
Publicado 2020

Local invertibility and sensitivity of atomic structure-feature mappings [version 1; peer review: 2 approved]

por Sergey N. Pozdnyakov, Liwei Zhang, Christoph Ortner, Gábor Csányi, Michele Ceriotti
Publicado 2021

Gaussian Process States: A Data-Driven Representation of Quantum Many-Body Physics

por Aldo Glielmo, Yannic Rath, Gábor Csányi, Alessandro De Vita, George H. Booth
Publicado 2020

Discovering the building blocks of atomic systems using machine learning: application to grain boundaries

por Conrad W. Rosenbrock, Eric R. Homer, Gábor Csányi, Gus L. W. Hart
Publicado 2017

Machine-learned interatomic potentials for alloys and alloy phase diagrams

por Conrad W. Rosenbrock, Konstantin Gubaev, Alexander V. Shapeev, Livia B. Pártay, Noam Bernstein, Gábor Csányi, Gus L. W. Hart
Publicado 2021

Performant implementation of the atomic cluster expansion (PACE) and application to copper and silicon

por Yury Lysogorskiy, Cas van der Oord, Anton Bochkarev, Sarath Menon, Matteo Rinaldi, Thomas Hammerschmidt, Matous Mrovec, Aidan Thompson, Gábor Csányi, Christoph Ortner, Ralf Drautz
Publicado 2021