PANNA: properties from artificial neural network architectures

DOI10.1016/j.cpc.2020.107402arXiv1907.03055OpenAlexW2955651397MaRDI QIDQ6040079

Emine Küçükbenli, Ruggero Lot, Yusuf Shaidu, Franco Pellegrini

Publication date: 24 May 2023

Published in: Computer Physics Communications (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1907.03055

zbMATH Keywords

neural networkmolecular dynamicsmachine learningforce fieldpotential-energy surface

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Software, source code, etc. for problems pertaining to statistical mechanics (82-04) Computational molecular dynamics in statistical mechanics (82M37)

Cites Work

• Fast parallel algorithms for short-range molecular dynamics
• sGDML: constructing accurate and data efficient molecular force fields using machine learning
• Principal component analysis: a review and recent developments
• Wavelet Scattering Regression of Quantum Chemical Energies
• Unnamed Item

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