Cormorant: Covariant Molecular Neural Networks

6 June 2019

Papers citing "Cormorant: Covariant Molecular Neural Networks"

50 / 250 papers shown

Title
Symmetry Group Equivariant Architectures for Physics A. Bogatskiy S. Ganguly Thomas Kipf Risi Kondor David W. Miller ... Jan T. Offermann M. Pettee P. Shanahan C. Shimmin S. Thais AI4CE 21 27 0 11 Mar 2022
Equivariant Graph Attention Networks for Molecular Property Prediction Tuan Le Frank Noé Djork-Arné Clevert 16 21 0 20 Feb 2022
Unsupervised Learning of Group Invariant and Equivariant Representations R. Winter Marco Bertolini Tuan Le Frank Noé Djork-Arné Clevert 25 40 0 15 Feb 2022
TorchMD-NET: Equivariant Transformers for Neural Network based Molecular Potentials Philipp Thölke Gianni de Fabritiis AI4CE 34 185 0 05 Feb 2022
ConDor: Self-Supervised Canonicalization of 3D Pose for Partial Shapes Rahul Sajnani A. Poulenard Jivitesh Jain Radhika Dua Leonidas J. Guibas Srinath Sridhar 3DPC 19 33 0 19 Jan 2022
Residual Pathway Priors for Soft Equivariance Constraints Marc Finzi Gregory W. Benton A. Wilson BDL UQCV 24 50 0 02 Dec 2021
Equivariant graph neural networks for fast electron density estimation of molecules, liquids, and solids Peter Bjørn Jørgensen Arghya Bhowmik 16 36 0 01 Dec 2021
Deformation Robust Roto-Scale-Translation Equivariant CNNs Liyao (Mars) Gao Guang Lin Wei-wei Zhu 20 8 0 22 Nov 2021
Directional Message Passing on Molecular Graphs via Synthetic Coordinates Johannes Klicpera Chandan Yeshwanth Stephan Günnemann 42 35 0 08 Nov 2021
SE(3) Equivariant Graph Neural Networks with Complete Local Frames Weitao Du He Zhang Yuanqi Du Qi Meng Wei-Neng Chen Bin Shao Tie-Yan Liu 56 79 0 26 Oct 2021
Geometric Transformer for End-to-End Molecule Properties Prediction Yoni Choukroun Lior Wolf AI4CE ViT 25 16 0 26 Oct 2021
Nested Graph Neural Networks Muhan Zhang Pan Li 27 163 0 25 Oct 2021
Capacity of Group-invariant Linear Readouts from Equivariant Representations: How Many Objects can be Linearly Classified Under All Possible Views? M. Farrell Blake Bordelon Shubhendu Trivedi C. Pehlevan 18 5 0 14 Oct 2021
Implicit Bias of Linear Equivariant Networks Hannah Lawrence Kristian Georgiev A. Dienes B. Kiani AI4CE 37 14 0 12 Oct 2021
Relative Molecule Self-Attention Transformer Lukasz Maziarka Dawid Majchrowski Tomasz Danel Piotr Gaiñski Jacek Tabor Igor T. Podolak Pawel M. Morkisz Stanislaw Jastrzebski MedIm 34 34 0 12 Oct 2021
A simple equivariant machine learning method for dynamics based on scalars Weichi Yao Kate Storey-Fisher D. Hogg Soledad Villar AI4CE 39 9 0 07 Oct 2021
Geometric and Physical Quantities Improve E(3) Equivariant Message Passing Johannes Brandstetter Rob D. Hesselink Elise van der Pol Erik J. Bekkers Max Welling 17 229 0 06 Oct 2021
Geometric Algebra Attention Networks for Small Point Clouds Matthew Spellings 3DPC 50 12 0 05 Oct 2021
Combining Physics and Deep Learning to learn Continuous-Time Dynamics Models M. Lutter Jan Peters PINN AI4CE 33 39 0 05 Oct 2021
Molformer: Motif-based Transformer on 3D Heterogeneous Molecular Graphs Fang Wu Dragomir R. Radev Huabin Xing ViT 36 54 0 04 Oct 2021
Reconstruction for Powerful Graph Representations Leonardo Cotta Christopher Morris Bruno Ribeiro AI4CE 130 78 0 01 Oct 2021
Efficient Differentiable Simulation of Articulated Bodies Yi-Ling Qiao Junbang Liang V. Koltun Ming Lin AI4CE 40 55 0 16 Sep 2021
Federated Learning of Molecular Properties with Graph Neural Networks in a Heterogeneous Setting Wei-wei Zhu Jiebo Luo Andrew D. White FedML 30 32 0 15 Sep 2021
Differentiable Physics: A Position Piece Bharath Ramsundar Dilip Krishnamurthy V. Viswanathan PINN AI4CE 37 14 0 14 Sep 2021
Heterogeneous relational message passing networks for molecular dynamics simulations Zun Wang Chong Wang Sibo Zhao Yong Xu Shaogang Hao Chang-Yu Hsieh B. Gu W. Duan 16 25 0 02 Sep 2021
6DCNN with roto-translational convolution filters for volumetric data processing Dmitrii Zhemchuzhnikov Ilia Igashov Sergei Grudinin 3DPC 27 2 0 26 Jul 2021
Geometric Deep Learning on Molecular Representations Kenneth Atz F. Grisoni G. Schneider AI4CE 34 287 0 26 Jul 2021
Physics-Guided Deep Learning for Dynamical Systems: A Survey Rui Wang Rose Yu AI4CE PINN 39 64 0 02 Jul 2021
GeoT: A Geometry-aware Transformer for Reliable Molecular Property Prediction and Chemically Interpretable Representation Learning Bumju Kwak J. Park Taewon Kang Jeonghee Jo Byunghan Lee Sungroh Yoon AI4CE 21 6 0 29 Jun 2021
Rotation Invariant Graph Neural Networks using Spin Convolutions Muhammed Shuaibi Adeesh Kolluru Abhishek Das Aditya Grover Anuroop Sriram Zachary W. Ulissi C. L. Zitnick AI4CE 27 67 0 17 Jun 2021
Simple GNN Regularisation for 3D Molecular Property Prediction & Beyond Jonathan Godwin Michael Schaarschmidt Alex Gaunt Alvaro Sanchez-Gonzalez Yulia Rubanova Petar Velivcković J. Kirkpatrick Peter W. Battaglia 39 60 0 15 Jun 2021
Flexible dual-branched message passing neural network for quantum mechanical property prediction with molecular conformation Jeonghee Jo Bumju Kwak Byunghan Lee Sungroh Yoon 16 2 0 14 Jun 2021
Equivariant Networks for Pixelized Spheres Mehran Shakerinava Siamak Ravanbakhsh 3DPC 25 19 0 12 Jun 2021
Scalars are universal: Equivariant machine learning, structured like classical physics Soledad Villar D. Hogg Kate Storey-Fisher Weichi Yao Ben Blum-Smith PINN AI4CE 24 130 0 11 Jun 2021
Equivariant Graph Neural Networks for 3D Macromolecular Structure Bowen Jing Stephan Eismann Pratham N. Soni R. Dror 6 95 0 07 Jun 2021
Detect the Interactions that Matter in Matter: Geometric Attention for Many-Body Systems Thorben Frank Stefan Chmiela 15 3 0 04 Jun 2021
SE(3)-equivariant prediction of molecular wavefunctions and electronic densities Oliver T. Unke Mihail Bogojeski M. Gastegger Mario Geiger Tess E. Smidt Klaus-Robert Muller 29 86 0 04 Jun 2021
Steerable 3D Spherical Neurons Pavlo Melnyk M. Felsberg Mårten Wadenbäck 3DPC LLMSV 21 5 0 02 Jun 2021
GemNet: Universal Directional Graph Neural Networks for Molecules Johannes Klicpera Florian Becker Stephan Günnemann AI4CE 24 434 0 02 Jun 2021
Symmetry-via-Duality: Invariant Neural Network Densities from Parameter-Space Correlators Anindita Maiti Keegan Stoner James Halverson 23 20 0 01 Jun 2021
Informing Geometric Deep Learning with Electronic Interactions to Accelerate Quantum Chemistry Zhuoran Qiao Anders S. Christensen Matthew Welborn F. Manby Anima Anandkumar Thomas F. Miller 16 74 0 31 May 2021
E(n) Equivariant Normalizing Flows Victor Garcia Satorras Emiel Hoogeboom F. Fuchs Ingmar Posner Max Welling BDL 34 168 0 19 May 2021
Optimal radial basis for density-based atomic representations Alexander Goscinski Félix Musil Sergey Pozdnyakov Michele Ceriotti 13 17 0 18 May 2021
Protein sequence-to-structure learning: Is this the end(-to-end revolution)? É. Laine Stephan Eismann A. Elofsson Sergei Grudinin OOD 3DV 23 34 0 16 May 2021
Towards Error Measures which Influence a Learners Inductive Bias to the Ground Truth A. I. Parkes A. J. Sobey D. Hudson UQCV 10 1 0 04 May 2021
SpookyNet: Learning Force Fields with Electronic Degrees of Freedom and Nonlocal Effects Oliver T. Unke Stefan Chmiela M. Gastegger Kristof T. Schütt H. E. Sauceda K. Müller 171 246 0 01 May 2021
Vector Neurons: A General Framework for SO(3)-Equivariant Networks Congyue Deng Or Litany Yueqi Duan A. Poulenard Andrea Tagliasacchi Leonidas J. Guibas 3DPC 111 315 0 25 Apr 2021
A Practical Method for Constructing Equivariant Multilayer Perceptrons for Arbitrary Matrix Groups Marc Finzi Max Welling A. Wilson 76 185 0 19 Apr 2021
Neural Pharmacodynamic State Space Modeling Zeshan Hussain Rahul G. Krishnan David Sontag BDL AI4CE 19 10 0 22 Feb 2021
Meta-Learning Dynamics Forecasting Using Task Inference Rui Wang Robin G. Walters Rose Yu OOD AI4TS AI4CE 24 31 0 20 Feb 2021