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Kristof T. Schütt

  1. Quantum-chemical insights from deep tensor neural networks
    2016/09/27 by Kristof T. Schütt, Farhad Arbabzadah, Stefan Chmiela +3 · 1 voice · 80 citations
    Materials Science · Biochemistry, Genetics and Molecular Biology · Computer Science · #Machine Learning in Materials Science #Protein Structure and Dynamics #Computational Drug Discovery Methods
  2. SchNet – A deep learning architecture for molecules and materials
    2018/03/29 by Kristof T. Schütt, K. T. Schütt, Huziel E. Sauceda +7 · 148 citations
    Materials Science · Computer Science · Biochemistry, Genetics and Molecular Biology · #Machine Learning in Materials Science #Computational Drug Discovery Methods #Protein Structure and Dynamics
  3. 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 · 60 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
  4. Symmetry-adapted generation of 3d point sets for the targeted discovery of molecules
    2019/06/02 by Niklas W. A. Gebauer, Gebauer, Niklas W. A., Michael Gastegger +3 · 21 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
  5. Learning how to explain neural networks: PatternNet and PatternAttribution
    2017/05/16 by Pieter Jan Kindermans, Kristof T. Schütt, Kindermans, Pieter-Jan +11 · 28 citations
    Computer Science · #Neural Networks and Applications
  6. Unifying machine learning and quantum chemistry -- a deep neural network for molecular wavefunctions
    2019/06/24 by Kristof T. Schütt, Michael Gastegger, Schütt, K. T. +7 · 12 citations
    Materials Science · Computer Science · Biochemistry, Genetics and Molecular Biology · #Machine Learning in Materials Science #Computational Drug Discovery Methods #Protein Structure and Dynamics
  7. iNNvestigate neural networks!
    2018/08/13 by Maximilian Alber, Sebastian Lapuschkin, Alber, Maximilian +17 · 6 citations
    Computer Science · #Explainable Artificial Intelligence (XAI) #Advanced Neural Network Applications #Adversarial Robustness in Machine Learning
  8. Investigating the influence of noise and distractors on the interpretation of neural networks
    2016/11/22 by Pieter-Jan Kindermans, Kristof T. Schütt, Kindermans, Pieter-Jan +5 · 2 citations
    Biochemistry, Genetics and Molecular Biology · Computer Science · #Adversarial Robustness in Machine Learning #Cell Image Analysis Techniques #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  9. PILOT: Equivariant diffusion for pocket conditioned de novo ligand generation with multi-objective guidance via importance sampling
    2024/05/23 by Julian Cremer, Tuan Le, Cremer, Julian +7 · 5 citations
    Materials Science · Computer Science · Medicine · #Crystallization and Solubility Studies #Gaussian Processes and Bayesian Inference #Tuberculosis Research and Epidemiology
  10. 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