Reducing SO(3) Convolutions to SO(2) for Efficient Equivariant GNNs

7 February 2023

Papers citing "Reducing SO(3) Convolutions to SO(2) for Efficient Equivariant GNNs"

48 / 48 papers shown

Title
SE(3)-Equivariant Robot Learning and Control: A Tutorial Survey Joohwan Seo Soochul Yoo Junwoo Chang Hyunseok An Hyunwoo Ryu Soomi Lee Arvind Kruthiventy Jongeun Choi R. Horowitz 71 2 0 12 Mar 2025
Enhancing the Scalability and Applicability of Kohn-Sham Hamiltonians for Molecular Systems Yunyang Li Zaishuo Xia Lin Huang Xinran Wei Han Yang ... Zun Wang Chang-Shu Liu Jia Zhang Bin Shao Mark B. Gerstein 77 0 0 26 Feb 2025
Equivariant Masked Position Prediction for Efficient Molecular Representation Junyi An C. Qu Yun-Fei Shi XinHao Liu Qianwei Tang Fenglei Cao Yuan Qi 40 0 0 12 Feb 2025
Learning local equivariant representations for quantum operators Zhanghao Zhouyin Zixi Gan MingKang Liu S. K. Pandey Linfeng Zhang Qiangqiang Gu 85 3 0 28 Jan 2025
Bridging Geometric States via Geometric Diffusion Bridge Shengjie Luo Yixian Xu Di He Shuxin Zheng Tie-Yan Liu Liwei Wang 37 0 0 31 Oct 2024
The Importance of Being Scalable: Improving the Speed and Accuracy of Neural Network Interatomic Potentials Across Chemical Domains Eric Qu Aditi S. Krishnapriyan LRM 30 10 0 31 Oct 2024
FlowLLM: Flow Matching for Material Generation with Large Language Models as Base Distributions Anuroop Sriram Benjamin Kurt Miller Ricky T. Q. Chen Brandon M. Wood AI4CE 42 14 0 30 Oct 2024
ET-Flow: Equivariant Flow-Matching for Molecular Conformer Generation Majdi Hassan Nikhil Shenoy Jungyoon Lee Hannes Stärk Stephan Thaler Dominique Beaini 29 6 0 29 Oct 2024
Open Materials 2024 (OMat24) Inorganic Materials Dataset and Models Luis Barroso-Luque Muhammed Shuaibi Xiang Fu Brandon M. Wood Misko Dzamba Meng Gao Ammar Rizvi C. L. Zitnick Zachary W. Ulissi AI4CE PINN 38 16 0 16 Oct 2024
Deconstructing equivariant representations in molecular systems Kin Long Kelvin Lee Mikhail Galkin Santiago Miret 30 2 0 10 Oct 2024
Learning Equivariant Non-Local Electron Density Functionals Nicholas Gao Eike Eberhard Stephan Günnemann 28 1 0 10 Oct 2024
On the design space between molecular mechanics and machine learning force fields Yuanqing Wang Kenichiro Takaba Michael S. Chen Marcus Wieder Yuzhi Xu ... Kyunghyun Cho Joe G. Greener Peter K. Eastman Stefano Martiniani M. Tuckerman AI4CE 42 4 0 03 Sep 2024
Improving Equivariant Model Training via Constraint Relaxation Stefanos Pertigkiozoglou Evangelos Chatzipantazis Shubhendu Trivedi Kostas Daniilidis 42 4 0 23 Aug 2024
Physics-Informed Weakly Supervised Learning for Interatomic Potentials Makoto Takamoto Viktor Zaverkin Mathias Niepert AI4CE 60 0 0 23 Jul 2024
SE(3)-bi-equivariant Transformers for Point Cloud Assembly Ziming Wang Rebecka Jörnsten 3DPC 43 2 0 12 Jul 2024
OrbitGrasp: $SE(3)$ -Equivariant Grasp Learning Boce Hu Xupeng Zhu Dian Wang Zihao Dong Haojie Huang Chenghao Wang Robin Walters Robert Platt 3DPC 28 9 0 03 Jul 2024
GeoMFormer: A General Architecture for Geometric Molecular Representation Learning Tianlang Chen Shengjie Luo Di He Shuxin Zheng Tie-Yan Liu Liwei Wang AI4CE 38 5 0 24 Jun 2024
NeuralSCF: Neural network self-consistent fields for density functional theory Feitong Song Ji Feng 36 0 0 22 Jun 2024
FlowMM: Generating Materials with Riemannian Flow Matching Benjamin Kurt Miller Ricky T. Q. Chen Anuroop Sriram Brandon M. Wood 31 33 0 07 Jun 2024
Flexible SE(2) graph neural networks with applications to PDE surrogates Maria Bånkestad Olof Mogren Aleksis Pirinen 56 1 0 30 May 2024
A Recipe for Charge Density Prediction Xiang Fu Andrew S. Rosen Kyle Bystrom Rui Wang Albert Musaelian Boris Kozinsky Tess E. Smidt Tommi Jaakkola 50 5 0 29 May 2024
Steerable Transformers Soumyabrata Kundu Risi Kondor ViT LLMSV 30 1 0 24 May 2024
Higher-Rank Irreducible Cartesian Tensors for Equivariant Message Passing Viktor Zaverkin Francesco Alesiani Takashi Maruyama Federico Errica Henrik Christiansen Makoto Takamoto Nicolas Weber Mathias Niepert 49 5 0 23 May 2024
Complete and Efficient Graph Transformers for Crystal Material Property Prediction Keqiang Yan Cong Fu Xiaofeng Qian Xiaoning Qian Shuiwang Ji 43 19 0 18 Mar 2024
Generalizing Denoising to Non-Equilibrium Structures Improves Equivariant Force Fields Yi-Lun Liao Tess E. Smidt Abhishek Das DiffM AI4CE 37 12 0 14 Mar 2024
A Survey of Geometric Graph Neural Networks: Data Structures, Models and Applications Jiaqi Han Jiacheng Cen Liming Wu Zongzhao Li Xiangzhe Kong ... Zhewei Wei Deli Zhao Yu Rong Wenbing Huang Wenbing Huang AI4CE 34 20 0 01 Mar 2024
Equivariant Frames and the Impossibility of Continuous Canonicalization Nadav Dym Hannah Lawrence Jonathan W. Siegel 38 17 0 25 Feb 2024
Enabling Efficient Equivariant Operations in the Fourier Basis via Gaunt Tensor Products Shengjie Luo Tianlang Chen Aditi S. Krishnapriyan 30 19 0 18 Jan 2024
Towards Harmonization of SO(3)-Equivariance and Expressiveness: a Hybrid Deep Learning Framework for Electronic-Structure Hamiltonian Prediction Shi Yin Xinyang Pan Xudong Zhu Tianyu Gao Haochong Zhang Feng Wu Lixin He 43 2 0 01 Jan 2024
Higher-Order Equivariant Neural Networks for Charge Density Prediction in Materials Teddy Koker Keegan Quigley Eric Taw Kevin Tibbetts Lin Li 20 12 0 08 Dec 2023
Uncertainty-biased molecular dynamics for learning uniformly accurate interatomic potentials Viktor Zaverkin David Holzmüller Henrik Christiansen Federico Errica Francesco Alesiani Makoto Takamoto Mathias Niepert Johannes Kastner AI4CE 29 13 0 03 Dec 2023
The Open DAC 2023 Dataset and Challenges for Sorbent Discovery in Direct Air Capture Anuroop Sriram Sihoon Choi Xiaohan Yu Logan M. Brabson Abhishek Das Zachary W. Ulissi Matthew Uyttendaele A. Medford D. Sholl AI4CE 27 35 0 01 Nov 2023
On the importance of catalyst-adsorbate 3D interactions for relaxed energy predictions Alvaro Carbonero Alexandre Duval Victor Schmidt Santiago Miret Alex Hernandez-Garcia Yoshua Bengio David Rolnick 32 0 0 10 Oct 2023
Discovering Symmetry Breaking in Physical Systems with Relaxed Group Convolution Rui Wang E. Hofgard Han Gao Robin Walters Tess E. Smidt AI4CE 34 9 0 03 Oct 2023
On Training Derivative-Constrained Neural Networks KaiChieh Lo Daniel Huang 26 3 0 02 Oct 2023
From Peptides to Nanostructures: A Euclidean Transformer for Fast and Stable Machine Learned Force Fields J. Frank Oliver T. Unke Klaus-Robert Muller Stefan Chmiela 26 3 0 21 Sep 2023
Matbench Discovery -- A framework to evaluate machine learning crystal stability predictions Janosh Riebesell Rhys E. A. Goodall Philipp Benner Chiang Yuan Bowen Deng A. Lee Anubhav Jain Kristin A. Persson OOD 36 35 0 28 Aug 2023
Equivariant Single View Pose Prediction Via Induced and Restricted Representations Owen Howell David M. Klee Ondrej Biza Linfeng Zhao Robin G. Walters 30 4 0 07 Jul 2023
Accelerating Molecular Graph Neural Networks via Knowledge Distillation Filip Ekstrom Kelvinius D. Georgiev Artur P. Toshev Johannes Gasteiger 26 7 0 26 Jun 2023
EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations Yidong Liao Brandon M. Wood Abhishek Das Tess E. Smidt 26 131 0 21 Jun 2023
AdsorbML: A Leap in Efficiency for Adsorption Energy Calculations using Generalizable Machine Learning Potentials Janice Lan Aini Palizhati Muhammed Shuaibi Brandon M. Wood Brook Wander Abhishek Das M. Uyttendaele C. L. Zitnick Zachary W. Ulissi 29 44 0 29 Nov 2022
Spherical Channels for Modeling Atomic Interactions C. L. Zitnick Abhishek Das Adeesh Kolluru Janice Lan Muhammed Shuaibi Anuroop Sriram Zachary W. Ulissi Brandon M. Wood 79 58 0 29 Jun 2022
Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs Yi-Lun Liao Tess E. Smidt 80 215 0 23 Jun 2022
Frame Averaging for Invariant and Equivariant Network Design Omri Puny Matan Atzmon Heli Ben-Hamu Ishan Misra Aditya Grover Edward James Smith Y. Lipman FedML 49 128 0 07 Oct 2021
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges M. Bronstein Joan Bruna Taco S. Cohen Petar Velivcković GNN 174 1,106 0 27 Apr 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
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 203 1,238 0 08 Jan 2021
The Open Catalyst 2020 (OC20) Dataset and Community Challenges L. Chanussot Abhishek Das Siddharth Goyal Thibaut Lavril Muhammed Shuaibi ... Brandon M. Wood Junwoong Yoon Devi Parikh C. L. Zitnick Zachary W. Ulissi 232 503 0 20 Oct 2020