N-body Networks: a Covariant Hierarchical Neural Network Architecture for Learning Atomic Potentials

5 March 2018

Papers citing "N-body Networks: a Covariant Hierarchical Neural Network Architecture for Learning Atomic Potentials"

35 / 35 papers shown

Title
EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling Theodoros Kouzelis Ioannis Kakogeorgiou Spyros Gidaris N. Komodakis DRL 80 5 0 17 Feb 2025
Learning local equivariant representations for quantum operators Zhanghao Zhouyin Zixi Gan MingKang Liu S. K. Pandey Linfeng Zhang Qiangqiang Gu 93 3 0 28 Jan 2025
On the Fourier analysis in the SO(3) space : EquiLoPO Network Dmitrii Zhemchuzhnikov Sergei Grudinin 50 0 0 24 Apr 2024
Equivalence Between SE(3) Equivariant Networks via Steerable Kernels and Group Convolution A. Poulenard M. Ovsjanikov Leonidas J. Guibas 3DPC 32 2 0 29 Nov 2022
Unifying O(3) Equivariant Neural Networks Design with Tensor-Network Formalism Zimu Li Zihan Pengmei Han Zheng Erik H. Thiede Junyu Liu Risi Kondor 29 2 0 14 Nov 2022
MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields Ilyes Batatia D. P. Kovács G. Simm Christoph Ortner Gábor Csányi 47 442 0 15 Jun 2022
Dimensionless machine learning: Imposing exact units equivariance Soledad Villar Weichi Yao D. Hogg Ben Blum-Smith Bianca Dumitrascu 18 26 0 02 Apr 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
Deformation Robust Roto-Scale-Translation Equivariant CNNs Liyao (Mars) Gao Guang Lin Wei-wei Zhu 25 8 0 22 Nov 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
DISCO: accurate Discrete Scale Convolutions Ivan Sosnovik A. Moskalev A. Smeulders 26 31 0 04 Jun 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
E(3)-Equivariant Graph Neural Networks for Data-Efficient and Accurate Interatomic Potentials Simon L. Batzner Albert Musaelian Lixin Sun Mario Geiger J. Mailoa M. Kornbluth N. Molinari Tess E. Smidt Boris Kozinsky 233 1,240 0 08 Jan 2021
Data-driven rogue waves and parameter discovery in the defocusing NLS equation with a potential using the PINN deep learning Li Wang Zhenya Yan 19 80 0 18 Dec 2020
A Wigner-Eckart Theorem for Group Equivariant Convolution Kernels Leon Lang Maurice Weiler 35 53 0 21 Oct 2020
On the Universality of Rotation Equivariant Point Cloud Networks Nadav Dym Haggai Maron 3DPC 38 79 0 06 Oct 2020
SE(3)-Transformers: 3D Roto-Translation Equivariant Attention Networks F. Fuchs Daniel E. Worrall Volker Fischer Max Welling 3DPC 45 666 0 18 Jun 2020
Lorentz Group Equivariant Neural Network for Particle Physics A. Bogatskiy Brandon M. Anderson Jan T. Offermann M. Roussi David W. Miller Risi Kondor AI4CE 29 136 0 08 Jun 2020
Isometric Transformation Invariant and Equivariant Graph Convolutional Networks Masanobu Horie Naoki Morita Toshiaki Hishinuma Yushi Ihara Naoto Mitsume GNN 8 23 0 13 May 2020
Theoretical Aspects of Group Equivariant Neural Networks Carlos Esteves 27 41 0 10 Apr 2020
Representations of molecules and materials for interpolation of quantum-mechanical simulations via machine learning Marcel F. Langer Alex Goessmann M. Rupp AI4CE 23 92 0 26 Mar 2020
On Learning Sets of Symmetric Elements Haggai Maron Or Litany Gal Chechik Ethan Fetaya 30 132 0 20 Feb 2020
Representation Learning on Unit Ball with 3D Roto-Translational Equivariance Sameera Ramasinghe Salman Khan Nick Barnes Stephen Gould 16 8 0 30 Nov 2019
Deep Learning for 2D and 3D Rotatable Data: An Overview of Methods Luca Della Libera Vladimir Golkov Yue Zhu Arman Mielke Daniel Cremers 3DH 3DPC 25 4 0 31 Oct 2019
Cormorant: Covariant Molecular Neural Networks Brandon M. Anderson Truong-Son Hy Risi Kondor 30 421 0 06 Jun 2019
Discrete Rotation Equivariance for Point Cloud Recognition Jiaxin Li Yingcai Bi Gim Hee Lee 3DPC 27 24 0 31 Mar 2019
Deep Learning on Attributed Graphs: A Journey from Graphs to Their Embeddings and Back M. Simonovsky BDL GNN 29 1 0 24 Jan 2019
A General Theory of Equivariant CNNs on Homogeneous Spaces Taco S. Cohen Mario Geiger Maurice Weiler MLT AI4CE 165 308 0 05 Nov 2018
Graph Neural Networks for IceCube Signal Classification Nicholas Choma Federico Monti Lisa Gerhardt T. Palczewski Z. Ronaghi P. Prabhat W. Bhimji M. Bronstein S. Klein Joan Bruna 16 76 0 17 Sep 2018
3D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Data Maurice Weiler Mario Geiger Max Welling Wouter Boomsma Taco S. Cohen 3DPC 45 494 0 06 Jul 2018
Clebsch-Gordan Nets: a Fully Fourier Space Spherical Convolutional Neural Network Risi Kondor Zhen Lin Shubhendu Trivedi 54 264 0 24 Jun 2018
Intertwiners between Induced Representations (with Applications to the Theory of Equivariant Neural Networks) Taco S. Cohen Mario Geiger Maurice Weiler 41 46 0 28 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 44 942 0 22 Feb 2018
On the Generalization of Equivariance and Convolution in Neural Networks to the Action of Compact Groups Risi Kondor Shubhendu Trivedi MLT 62 487 0 11 Feb 2018
Geometric deep learning on graphs and manifolds using mixture model CNNs Federico Monti Davide Boscaini Jonathan Masci Emanuele Rodolà Jan Svoboda M. Bronstein GNN 260 1,811 0 25 Nov 2016