E(3)-Equivariant Graph Neural Networks for Data-Efficient and Accurate Interatomic Potentials

8 January 2021

Papers citing "E(3)-Equivariant Graph Neural Networks for Data-Efficient and Accurate Interatomic Potentials"

46 / 396 papers shown

Title
The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials Ilyes Batatia Simon L. Batzner D. P. Kovács Albert Musaelian G. Simm R. Drautz Christoph Ortner Boris Kozinsky Gábor Csányi 32 133 0 13 May 2022
Low Dimensional Invariant Embeddings for Universal Geometric Learning Nadav Dym S. Gortler 29 39 0 05 May 2022
Simulate Time-integrated Coarse-grained Molecular Dynamics with Multi-Scale Graph Networks Xiang Fu T. Xie Nathan J. Rebello B. Olsen Tommi Jaakkola AI4CE 30 13 0 21 Apr 2022
Learning Local Equivariant Representations for Large-Scale Atomistic Dynamics Albert Musaelian Simon L. Batzner A. Johansson Lixin Sun Cameron J. Owen M. Kornbluth Boris Kozinsky 24 424 0 11 Apr 2022
GemNet-OC: Developing Graph Neural Networks for Large and Diverse Molecular Simulation Datasets Johannes Gasteiger Muhammed Shuaibi Anuroop Sriram Stephan Günnemann Zachary W. Ulissi C. L. Zitnick Abhishek Das AI4TS MLAU 36 66 0 06 Apr 2022
Dimensionless machine learning: Imposing exact units equivariance Soledad Villar Weichi Yao D. Hogg Ben Blum-Smith Bianca Dumitrascu 16 26 0 02 Apr 2022
Automatic Identification of Chemical Moieties Jonas Lederer M. Gastegger Kristof T. Schütt Michael C. Kampffmeyer Klaus-Robert Muller Oliver T. Unke 21 5 0 30 Mar 2022
Equivariant Point Cloud Analysis via Learning Orientations for Message Passing Shitong Luo Jiahan Li Jiaqi Guan Yufeng Su Chaoran Cheng Jian-wei Peng Jianzhu Ma 3DPC 26 34 0 28 Mar 2022
Symmetry-Based Representations for Artificial and Biological General Intelligence I. Higgins S. Racanière Danilo Jimenez Rezende AI4CE 31 44 0 17 Mar 2022
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 27 27 0 11 Mar 2022
GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation Minkai Xu Lantao Yu Yang Song Chence Shi Stefano Ermon Jian Tang BDL DiffM 50 496 0 06 Mar 2022
Spin-Dependent Graph Neural Network Potential for Magnetic Materials Hongyu Yu Yang Zhong Liangliang Hong Changsong Xu W. Ren X. Gong Hongjun Xiang 32 14 0 06 Mar 2022
Invariance Learning in Deep Neural Networks with Differentiable Laplace Approximations Alexander Immer Tycho F. A. van der Ouderaa Gunnar Rätsch Vincent Fortuin Mark van der Wilk BDL 39 44 0 22 Feb 2022
Equivariant Graph Attention Networks for Molecular Property Prediction Tuan Le Frank Noé Djork-Arné Clevert 16 21 0 20 Feb 2022
EquiBind: Geometric Deep Learning for Drug Binding Structure Prediction Hannes Stärk O. Ganea L. Pattanaik Regina Barzilay Tommi Jaakkola 22 262 0 07 Feb 2022
TorchMD-NET: Equivariant Transformers for Neural Network based Molecular Potentials Philipp Thölke Gianni De Fabritiis AI4CE 34 186 0 05 Feb 2022
Rigidity Preserving Image Transformations and Equivariance in Perspective Lucas Brynte Georg Bökman Axel Flinth Fredrik Kahl 40 3 0 31 Jan 2022
Compositionality as Lexical Symmetry Ekin Akyürek Jacob Andreas CoGe 52 8 0 30 Jan 2022
Generative Coarse-Graining of Molecular Conformations Wujie Wang Minkai Xu Chen Cai Benjamin Kurt Miller Tess E. Smidt Yusu Wang Jian Tang Rafael Gómez-Bombarelli 27 34 0 28 Jan 2022
NNP/MM: Accelerating molecular dynamics simulations with machine learning potentials and molecular mechanic Raimondas Galvelis Alejandro Varela-Rial Stefan Doerr R. Fino Peter K. Eastman T. Markland J. Chodera Gianni De Fabritiis 11 38 0 20 Jan 2022
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
SE(3) Equivariant Graph Neural Networks with Complete Local Frames Weitao Du He Zhang Yuanqi Du Qi Meng Wei Chen Bin Shao Tie-Yan Liu 56 79 0 26 Oct 2021
Surrogate- and invariance-boosted contrastive learning for data-scarce applications in science Charlotte Loh T. Christensen Rumen Dangovski Samuel Kim Marin Soljacic 32 16 0 15 Oct 2021
Ab-Initio Potential Energy Surfaces by Pairing GNNs with Neural Wave Functions Nicholas Gao Stephan Günnemann 27 36 0 11 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
Applying Machine Learning to Study Fluid Mechanics Steven L. Brunton PINN AI4CE 39 95 0 05 Oct 2021
Differentiable Physics: A Position Piece Bharath Ramsundar Dilip Krishnamurthy V. Viswanathan PINN AI4CE 40 14 0 14 Sep 2021
Inverse design of 3d molecular structures with conditional generative neural networks Niklas W. A. Gebauer M. Gastegger Stefaan S. P. Hessmann Klaus-Robert Muller Kristof T. Schütt AI4CE 192 166 0 10 Sep 2021
Supervised Learning and the Finite-Temperature String Method for Computing Committor Functions and Reaction Rates Muhammad R Hasyim Clay H. Batton K. Mandadapu 24 10 0 28 Jul 2021
Geometric Deep Learning on Molecular Representations Kenneth Atz F. Grisoni G. Schneider AI4CE 34 287 0 26 Jul 2021
Data efficiency in graph networks through equivariance Francesco Farina E. Slade 15 1 0 25 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 30 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 41 60 0 15 Jun 2021
Equivariant Graph Neural Networks for 3D Macromolecular Structure Bowen Jing Stephan Eismann Pratham N. Soni R. Dror 17 95 0 07 Jun 2021
Detect the Interactions that Matter in Matter: Geometric Attention for Many-Body Systems Thorben Frank Stefan Chmiela 23 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 31 86 0 04 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
Symmetry-driven graph neural networks Francesco Farina E. Slade 37 4 0 28 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 177 246 0 01 May 2021
Equivariant geometric learning for digital rock physics: estimating formation factor and effective permeability tensors from Morse graph Chen Cai Nikolaos N. Vlassis Lucas Magee R. Ma Zeyu Xiong B. Bahmani T. Wong Yusu Wang WaiChing Sun 22 16 0 12 Apr 2021
Beyond permutation equivariance in graph networks E. Slade Francesco Farina 29 3 0 25 Mar 2021
Spherical Message Passing for 3D Graph Networks Yi Liu Limei Wang Meng Liu Xuan Zhang Bora Oztekin Shuiwang Ji GNN 22 197 0 09 Feb 2021
Equivariant message passing for the prediction of tensorial properties and molecular spectra Kristof T. Schütt Oliver T. Unke M. Gastegger 36 512 0 05 Feb 2021
Boosting Deep Neural Networks with Geometrical Prior Knowledge: A Survey M. Rath A. P. Condurache ViT AI4CE 32 9 0 30 Jun 2020
TeaNet: universal neural network interatomic potential inspired by iterative electronic relaxations So Takamoto S. Izumi Ju Li GNN 29 76 0 02 Dec 2019