SchNet: A continuous-filter convolutional neural network for modeling quantum interactions

26 June 2017

Kristof T. Schütt

Pieter-Jan Kindermans

Huziel Enoc Sauceda Felix

Papers citing "SchNet: A continuous-filter convolutional neural network for modeling quantum interactions"

25 / 225 papers shown

Title
Machine learning for molecular simulation Frank Noé A. Tkatchenko K. Müller C. Clementi AI4CE 16 642 0 07 Nov 2019
Generating valid Euclidean distance matrices Moritz Hoffmann Frank Noé 21 56 0 07 Oct 2019
A Generative Model for Molecular Distance Geometry G. Simm José Miguel Hernández-Lobato GAN 24 107 0 25 Sep 2019
Deformable Filter Convolution for Point Cloud Reasoning Yuwen Xiong Mengye Ren Renjie Liao K. Wong R. Urtasun 3DPC 34 17 0 30 Jul 2019
Molecular Property Prediction: A Multilevel Quantum Interactions Modeling Perspective Chengqiang Lu Qi Liu Chao Wang Zhenya Huang Peize Lin Lixin He AI4CE 22 191 0 25 Jun 2019
Unifying machine learning and quantum chemistry -- a deep neural network for molecular wavefunctions Kristof T. Schütt M. Gastegger A. Tkatchenko K. Müller R. Maurer AI4CE 29 382 0 24 Jun 2019
Cormorant: Covariant Molecular Neural Networks Brandon M. Anderson Truong-Son Hy Risi Kondor 30 421 0 06 Jun 2019
Symmetry-adapted generation of 3d point sets for the targeted discovery of molecules Niklas W. A. Gebauer M. Gastegger Kristof T. Schütt 35 201 0 02 Jun 2019
Software and application patterns for explanation methods Maximilian Alber 33 11 0 09 Apr 2019
Unmasking Clever Hans Predictors and Assessing What Machines Really Learn Sebastian Lapuschkin S. Wäldchen Alexander Binder G. Montavon Wojciech Samek K. Müller 17 996 0 26 Feb 2019
Deep Learning on Attributed Graphs: A Journey from Graphs to Their Embeddings and Back M. Simonovsky BDL GNN 26 1 0 24 Jan 2019
Machine Learning for Molecular Dynamics on Long Timescales Frank Noé AI4CE 15 32 0 18 Dec 2018
Learning Multimodal Graph-to-Graph Translation for Molecular Optimization Wengong Jin Kevin Kaichuang Yang Regina Barzilay Tommi Jaakkola 33 224 0 03 Dec 2018
Active Learning of Uniformly Accurate Inter-atomic Potentials for Materials Simulation Linfeng Zhang De-Ye Lin Han Wang R. Car E. Weinan 9 326 0 28 Oct 2018
Generating equilibrium molecules with deep neural networks Niklas W. A. Gebauer M. Gastegger Kristof T. Schütt BDL 19 38 0 26 Oct 2018
Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks Christopher Morris Martin Ritzert Matthias Fey William L. Hamilton J. E. Lenssen Gaurav Rattan Martin Grohe GNN 97 1,606 0 04 Oct 2018
Quantum-chemical insights from interpretable atomistic neural networks Kristof T. Schütt M. Gastegger A. Tkatchenko K. Müller AI4CE 33 31 0 27 Jun 2018
Hierarchical Graph Representation Learning with Differentiable Pooling Rex Ying Jiaxuan You Christopher Morris Xiang Ren William L. Hamilton J. Leskovec GNN 84 2,124 0 22 Jun 2018
Neural Message Passing with Edge Updates for Predicting Properties of Molecules and Materials Peter Bjørn Jørgensen K. Jacobsen Mikkel N. Schmidt 30 82 0 08 Jun 2018
Solid Harmonic Wavelet Scattering for Predictions of Molecule Properties Michael Eickenberg Georgios Exarchakis M. Hirn S. Mallat L. Thiry 22 69 0 01 May 2018
Visualizing Convolutional Neural Network Protein-Ligand Scoring Joshua E. Hochuli Alec Helbling Tamar Skaist Matthew Ragoza D. Koes FAtt 16 65 0 06 Mar 2018
Tensor field networks: Rotation- and translation-equivariant neural networks for 3D point clouds Nathaniel Thomas Tess E. Smidt S. Kearnes Lusann Yang Li Li Kai Kohlhoff Patrick F. Riley 3DPC 39 941 0 22 Feb 2018
SplineCNN: Fast Geometric Deep Learning with Continuous B-Spline Kernels Matthias Fey J. E. Lenssen F. Weichert H. Müller 3DPC 36 437 0 24 Nov 2017
Ligand Pose Optimization with Atomic Grid-Based Convolutional Neural Networks Matthew Ragoza Lillian Turner D. Koes 32 16 0 20 Oct 2017
A Unifying View of Explicit and Implicit Feature Maps of Graph Kernels Nils M. Kriege Marion Neumann Christopher Morris Kristian Kersting Petra Mutzel 31 22 0 02 Mar 2017