Matthias Rupp

1. Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning
   2011/09/30 by Matthias Rupp, Alexandre Tkatchenko, Klaus‐Robert Müller +1 · 1 voice · 28 citations
   Computer Science · Materials Science · Physics and Astronomy · #Advanced Chemical Physics Studies #Computational Drug Discovery Methods #Machine Learning in Materials Science
2. Crash testing machine learning force fields for molecules, materials, and interfaces: model analysis in the TEA Challenge 2023
   2025/01/01 by Igor Poltavsky, Anton Charkin-Gorbulin, Mirela Puleva +23 · 1 voice · 7 citations
   Materials Science · Computer Science · #Machine Learning in Materials Science #Computational Drug Discovery Methods #Nuclear Materials and Properties
3. Fourier series of atomic radial distribution functions: A molecular fingerprint for machine learning models of quantum chemical properties
   2013/07/10 by O. Anatole von Lilienfeld, Raghunathan Ramakrishnan, von Lilienfeld, O. Anatole +5 · 2 citations
   Chemistry · Computer Science · Materials Science · #Chemical Physics (physics.chem-ph) #Computational Drug Discovery Methods #Crystallography and molecular interactions #FOS: Physical sciences #Machine Learning in Materials Science
4. Understanding Kernel Ridge Regression: Common behaviors from simple\n functions to density functionals
   2015/01/15 by Kevin Vu, Vu, Kevin, John Snyder +13 · 1 citation
   Materials Science · #Computational Physics (physics.comp-ph) #FOS: Computer and information sciences #FOS: Physical sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning in Materials Science
5. Hydrogen under Pressure as a Benchmark for Machine-Learning Interatomic Potentials
   2024/09/20 by Thomas Bischoff, Bischoff, Thomas, Bastian Jäckl +3 · 2 citations
   Earth and Planetary Sciences · Physics and Astronomy · #Cold Fusion and Nuclear Reactions #FOS: Computer and information sciences #FOS: Physical sciences #Machine Learning (cs.LG) #Materials Science (cond-mat.mtrl-sci) #Nuclear Physics and Applications #Quantum, superfluid, helium dynamics