Showing 1–20 of 24 results
/ Date/ Name
May 16, 2017Learning how to explain neural networks: PatternNet and PatternAttributionJun 2, 2019Symmetry-adapted generation of 3d point sets for the targeted discovery of moleculesOct 28, 2020Machine learning of solvent effects on molecular spectra and reactionsFeb 16, 2021Perspective on integrating machine learning into computational chemistry and materials scienceMay 1, 2021SpookyNet: Learning Force Fields with Electronic Degrees of Freedom and Nonlocal EffectsOct 14, 2020Machine Learning Force FieldsAug 13, 2018iNNvestigate neural networks!Jun 26, 2017SchNet: A continuous-filter convolutional neural network for modeling quantum interactionsMar 30, 2022Automatic Identification of Chemical MoietiesDec 11, 2018Learning representations of molecules and materials with atomistic neural networksJun 27, 2018Quantum-chemical insights from interpretable atomistic neural networksFeb 5, 2021Equivariant message passing for the prediction of tensorial properties and molecular spectraSep 10, 2021Inverse design of 3d molecular structures with conditional generative neural networksMay 23, 2024PILOT: Equivariant diffusion for pocket conditioned de novo ligand generation with multi-objective guidance via importance samplingFeb 27, 2020Autonomous robotic nanofabrication with reinforcement learningSep 27, 2016Quantum-Chemical Insights from Deep Tensor Neural NetworksNov 15, 2016Machine Learning of Accurate Energy-Conserving Molecular Force FieldsAug 7, 2024Accelerating crystal structure search through active learning with neural networks for rapid relaxationsDec 11, 2022SchNetPack 2.0: A neural network toolbox for atomistic machine learningOct 26, 2018Generating equilibrium molecules with deep neural networks