O. Anatole von Lilienfeld
University of Toronto(CA)Berlin Mathematical School(DE)Structural Genomics Consortium(CA)Vector Institute(CA)Division of Materials Science and Engineering(AU)Max Planck Institute for the History of Science(DE)Berlin Institute for the Foundations of Learning and DataTechnische Universität Berlin(DE)
Publications by Year
Research Areas
Machine Learning in Materials Science, Computational Drug Discovery Methods, Advanced Chemical Physics Studies, Various Chemistry Research Topics, Protein Structure and Dynamics
Most-Cited Works
- → Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning(2012)2,340 cited
- → Quantum chemistry structures and properties of 134 kilo molecules(2014)1,954 cited
- → Big Data Meets Quantum Chemistry Approximations: The Δ-Machine Learning Approach(2015)848 cited
- → Machine Learning Predictions of Molecular Properties: Accurate Many-Body Potentials and Nonlocality in Chemical Space(2015)838 cited
- → Prediction Errors of Molecular Machine Learning Models Lower than Hybrid DFT Error(2017)675 cited
- → Assessment and Validation of Machine Learning Methods for Predicting Molecular Atomization Energies(2013)634 cited