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Gastegger, Michael

  1. Equivariant message passing for the prediction of tensorial properties and molecular spectra
    2021/02/05 by Kristof T. Schütt, Schütt, Kristof T., Oliver T. Unke +3 · 64 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
  2. Symmetry-adapted generation of 3d point sets for the targeted discovery of molecules
    2019/06/02 by Niklas W. A. Gebauer, Michael Gastegger, Gebauer, Niklas W. A. +3 · 26 citations
    Biochemistry, Genetics and Molecular Biology · 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 (stat.ML) #Machine Learning in Materials Science #Protein Structure and Dynamics
  3. Fast protein backbone generation with SE(3) flow matching
    2023/10/08 by Jason Yim, Andrew M. Campbell, Andrew Campbell +21 · 1 voice · 24 citations
    Biochemistry, Genetics and Molecular Biology · Decision Sciences · Physics and Astronomy · #Model Reduction and Neural Networks #Protein Structure and Dynamics #Scientific Computing and Data Management #q-bio.QM
  4. SE(3)-equivariant prediction of molecular wavefunctions and electronic\n densities
    2021/06/04 by Oliver T. Unke, Mihail Bogojeski, Unke, Oliver T. +9 · 11 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
  5. Machine learning of solvent effects on molecular spectra and reactions
    2020/10/28 by Gastegger, Michael, Schütt, Kristof T., Müller, Klaus-Robert · 7 citations
    #Chemical Physics (physics.chem-ph) #FOS: Computer and information sciences #FOS: Physical sciences #Machine Learning (stat.ML)
  6. Molecular Dynamics with Neural-Network Potentials
    2018/12/18 by Michael Gastegger, Philipp Marquetand, Gastegger, Michael +1 · 2 citations
    Materials Science · Computer Science · Engineering · #Machine Learning in Materials Science #Computational Drug Discovery Methods #Advanced Chemical Sensor Technologies
  7. Accelerating crystal structure search through active learning with neural networks for rapid relaxations
    2024/08/07 by Stefaan S. P. Hessmann, Kristof T. Schütt, Hessmann, Stefaan S. P. +9 · 1 citation
    Materials Science · #X-ray Diffraction in Crystallography #Machine Learning in Materials Science #Crystallization and Solubility Studies