Unke, Oliver T.
- Equivariant message passing for the prediction of tensorial properties and molecular spectra
2021/02/05 by Kristof T. Schütt, Oliver T. Unke, Schütt, Kristof T. +3 · 81 citations
Biochemistry, Genetics and Molecular Biology · Computer Science · Materials Science · #Chemical Physics (physics.chem-ph) #Computational Drug Discovery Methods #FOS: Computer and information sciences #FOS: Physical sciences #Machine Learning (cs.LG) #Machine Learning in Materials Science #Protein Structure and Dynamics
- Accurate global machine learning force fields for molecules with hundreds of atoms
2022/09/29 by Stefan Chmiela, Valentín Vassilev-Galindo, Chmiela, Stefan +11 · 19 citations
Biochemistry, Genetics and Molecular Biology · Engineering · Materials Science · #Chemical Physics (physics.chem-ph) #Computational Physics (physics.comp-ph) #FOS: Physical sciences #Fuel Cells and Related Materials #Machine Learning in Materials Science #Protein Structure and Dynamics
- SE(3)-equivariant prediction of molecular wavefunctions and electronic\n densities
2021/06/04 by Oliver T. Unke, Unke, Oliver T., Mihail Bogojeski +9 · 13 citations
Biochemistry, Genetics and Molecular Biology · Chemistry · Computer Science · Materials Science · #Chemical Physics (physics.chem-ph) #FOS: Computer and information sciences #FOS: Physical sciences #Machine Learning (stat.ML) #Machine Learning in Materials Science #Protein Structure and Dynamics #Seismology and Earthquake Studies #Topic Modeling #Various Chemistry Research Topics
- So3krates: Equivariant attention for interactions on arbitrary length-scales in molecular systems
2022/05/28 by J. Thorben Frank, Frank, J. Thorben, Oliver T. Unke +3 · 10 citations
Chemistry · Computer Science · Materials Science · #Computational Drug Discovery Methods #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning in Materials Science #Various Chemistry Research Topics
- Roadmap on Advancements of the FHI-aims Software Package
2025/04/30 by Joseph W. Abbott, Abbott, Joseph W., Carlos Mera Acosta +405 · 3 voices · 7 citations
#cond-mat.mtrl-sci #physics.chem-ph
- Euclidean Fast Attention -- Machine Learning Global Atomic Representations at Linear Cost
2024/12/11 by J. Thorben Frank, Frank, J. Thorben, Stefan Chmiela +5 · 8 citations
Materials Science · #Electron and X-Ray Spectroscopy Techniques #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning in Materials Science #X-ray Diffraction in Crystallography
- How simple can you go? An off-the-shelf transformer approach to molecular dynamics
2025/03/03 by Max Eissler, Eissler, Max, Tim Korjakow +9 · 5 citations
Computer Science · Materials Science · Physics and Astronomy · #Advanced Graph Neural Networks #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning in Materials Science #Quantum many-body systems
- Complete and Efficient Covariants for 3D Point Configurations with Application to Learning Molecular Quantum Properties
2024/09/04 by Hartmut Maennel, Oliver T. Unke, Maennel, Hartmut +3 · 1 citation
Computer Science · Materials Science · #Chemical Physics (physics.chem-ph) #FOS: Computer and information sciences #FOS: Physical sciences #Machine Learning (cs.LG) #Machine Learning and Algorithms #Machine Learning in Materials Science
- Sampling 3D Molecular Conformers with Diffusion Transformers
2025/06/18 by J. Thorben Frank, Winfried Ripken, Frank, J. Thorben +9 · 1 citation
Chemical Engineering · Chemistry · Pharmacology, Toxicology and Pharmaceutics · #Catalysis and Oxidation Reactions #Chemical Reactions and Isotopes #Crystallography and molecular interactions #FOS: Computer and information sciences #Machine Learning (cs.LG)