Johannes T. Margraf
- A foundation model for atomistic materials chemistry
2023/12/29 by Ilyes Batatia, Philipp Benner, Batatia, Ilyes +182 · 5 voices · 137 citations
Materials Science · Decision Sciences · #physics.chem-ph #cond-mat.mtrl-sci
- Fast and Uncertainty-Aware Directional Message Passing for Non-Equilibrium Molecules
2020/11/28 by Johannes Gasteiger, Gasteiger, Johannes, Shankari Giri +5 · 21 citations
Chemistry · Computer Science · Materials Science · #Chemical Physics (physics.chem-ph) #Computational Drug Discovery Methods #Computational Physics (physics.comp-ph) #FOS: Computer and information sciences #FOS: Physical sciences #Machine Learning (cs.LG) #Machine Learning in Materials Science #Mass Spectrometry Techniques and Applications
- Roadmap on Advancements of the FHI-aims Software Package
2025/04/30 by Joseph W. Abbott, Carlos Mera Acosta, Abbott, Joseph W. +405 · 3 voices · 7 citations
#cond-mat.mtrl-sci #physics.chem-ph
- 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 · 5 citations
Materials Science · Computer Science · #Machine Learning in Materials Science #Computational Drug Discovery Methods #Nuclear Materials and Properties
- Beyond Numerical Hessians: Higher-Order Derivatives for Machine Learning Interatomic Potentials via Automatic Differentiation
2025/04/25 by Nils Gönnheimer, Karsten Reuter, Johannes T. Margraf · 1 voice · 2 citations
Chemical Engineering · Materials Science · Physics and Astronomy · #Advanced Chemical Physics Studies #Catalysis and Oxidation Reactions #Machine Learning in Materials Science