Rotation Invariant Graph Neural Networks using Spin Convolutions

17 June 2021

Papers citing "Rotation Invariant Graph Neural Networks using Spin Convolutions"

45 / 45 papers shown

Title
MVGT: A Multi-view Graph Transformer Based on Spatial Relations for EEG Emotion Recognition Yanjie Cui Xiaohong Liu Jing Liang Yamin Fu 59 1 0 17 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
Distribution Learning for Molecular Regression Nima Shoghi Pooya Shoghi Anuroop Sriram Abhishek Das OOD 27 0 0 30 Jul 2024
Hashing based Contrastive Learning for Virtual Screening Jin Han Yun Hong Wu-Jun Li 18 0 0 29 Jul 2024
Physics-Informed Weakly Supervised Learning for Interatomic Potentials Makoto Takamoto Viktor Zaverkin Mathias Niepert AI4CE 60 0 0 23 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
Baking Symmetry into GFlowNets George Ma Emmanuel Bengio Yoshua Bengio Dinghuai Zhang 45 8 0 08 Jun 2024
MolBind: Multimodal Alignment of Language, Molecules, and Proteins Teng Xiao Chao Cui Huaisheng Zhu V. Honavar AI4CE 34 7 0 13 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
Impact of Domain Knowledge and Multi-Modality on Intelligent Molecular Property Prediction: A Systematic Survey Taojie Kuang Pengfei Liu Zhixiang Ren AI4CE 47 1 0 11 Feb 2024
Accelerating Material Property Prediction using Generically Complete Isometry Invariants Jonathan Balasingham Viktor Zamaraev V. Kurlin 14 5 0 22 Jan 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
PerCNet: Periodic Complete Representation for Crystal Graphs Jiao Huang Qianli Xing Jinglong Ji Bo Yang 34 1 0 03 Dec 2023
Gradual Optimization Learning for Conformational Energy Minimization Artem Tsypin L. Ugadiarov Kuzma Khrabrov Alexander Telepov Egor Rumiantsev Alexey Skrynnik Aleksandr I. Panov Dmitry Vetrov E. Tutubalina Artur Kadurin 24 1 0 05 Nov 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
Towards Combinatorial Generalization for Catalysts: A Kohn-Sham Charge-Density Approach Phillip Pope David Jacobs 24 3 0 28 Oct 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
FAENet: Frame Averaging Equivariant GNN for Materials Modeling Alexandre Duval Victor Schmidt A. Garcia Santiago Miret Fragkiskos D. Malliaros Yoshua Bengio David Rolnick 34 54 0 28 Apr 2023
3D Molecular Generation via Virtual Dynamics Shuqi Lu Lin Yao X. Chen Hang Zheng Di He Guolin Ke DiffM 26 7 0 12 Feb 2023
Reducing SO(3) Convolutions to SO(2) for Efficient Equivariant GNNs Saro Passaro C. L. Zitnick 3DPC 31 79 0 07 Feb 2023
Molecular Geometry-aware Transformer for accurate 3D Atomic System modeling Zheng Yuan Yaoyun Zhang Chuanqi Tan Wei Wang Feiran Huang Songfang Huang AI4CE ViT 24 6 0 02 Feb 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
PhAST: Physics-Aware, Scalable, and Task-specific GNNs for Accelerated Catalyst Design Alexandre Duval Victor Schmidt Santiago Miret Yoshua Bengio Alex Hernández-García David Rolnick 33 7 0 22 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
Why self-attention is Natural for Sequence-to-Sequence Problems? A Perspective from Symmetries Chao Ma Lexing Ying 22 2 0 13 Oct 2022
DPA-1: Pretraining of Attention-based Deep Potential Model for Molecular Simulation Duoduo Zhang Hangrui Bi Fu-Zhi Dai Wanrun Jiang Linfeng Zhang Han Wang AI4CE 32 37 0 17 Aug 2022
Boosting Heterogeneous Catalyst Discovery by Structurally Constrained Deep Learning Models A. Korovin Innokentiy S. Humonen A. Samtsevich R. Eremin Artem I. Vasilyev V. Lazarev S. Budennyy GNN 14 5 0 11 Jul 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
Molecular Geometry Pretraining with SE(3)-Invariant Denoising Distance Matching Shengchao Liu Hongyu Guo Jian Tang 23 77 0 27 Jun 2022
Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs Yi-Lun Liao Tess E. Smidt 80 215 0 23 Jun 2022
The Open Catalyst 2022 (OC22) Dataset and Challenges for Oxide Electrocatalysts Richard Tran Janice Lan Muhammed Shuaibi Brandon M. Wood Siddharth Goyal ... Jehad Abed Oleksandr Voznyy Edward H. Sargent Zachary W. Ulissi C. L. Zitnick 28 172 0 17 Jun 2022
ComENet: Towards Complete and Efficient Message Passing for 3D Molecular Graphs Limei Wang Yi Liu Yu-Ching Lin Hao Liu Shuiwang Ji GNN 38 89 0 17 Jun 2022
Pre-training via Denoising for Molecular Property Prediction Sheheryar Zaidi Michael Schaarschmidt James Martens Hyunjik Kim Yee Whye Teh Alvaro Sanchez-Gonzalez Peter W. Battaglia Razvan Pascanu Jonathan Godwin DiffM AI4CE 15 121 0 31 May 2022
FINETUNA: Fine-tuning Accelerated Molecular Simulations Joseph Musielewicz Xiaoxiao Wang Tian Tian Zachary W. Ulissi 19 32 0 02 May 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 33 66 0 06 Apr 2022
MolGenSurvey: A Systematic Survey in Machine Learning Models for Molecule Design Yuanqi Du Tianfan Fu Jimeng Sun Shengchao Liu AI4CE 31 86 0 28 Mar 2022
Towards Training Billion Parameter Graph Neural Networks for Atomic Simulations Anuroop Sriram Abhishek Das Brandon M. Wood Siddharth Goyal C. L. Zitnick AI4CE 30 27 0 18 Mar 2022
Benchmarking Graphormer on Large-Scale Molecular Modeling Datasets Yu Shi Shuxin Zheng Guolin Ke Yifei Shen Jiacheng You Jiyan He Shengjie Luo Chang-Shu Liu Di He Tie-Yan Liu AI4CE 42 65 0 09 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 24 496 0 06 Mar 2022
An Empirical Study of Graphormer on Large-Scale Molecular Modeling Datasets Yu Shi Shuxin Zheng Guolin Ke Yifei Shen Jiacheng You Jiyan He Shengjie Luo Chang-Shu Liu Di He Tie-Yan Liu AI4CE 8 0 0 28 Feb 2022
AlphaDesign: A graph protein design method and benchmark on AlphaFoldDB Zhangyang Gao Cheng Tan Stan Z. Li 144 52 0 01 Feb 2022
Crystal Diffusion Variational Autoencoder for Periodic Material Generation Tian Xie Xiang Fu O. Ganea Regina Barzilay Tommi Jaakkola DiffM BDL 212 232 0 12 Oct 2021
GemNet: Universal Directional Graph Neural Networks for Molecules Johannes Klicpera Florian Becker Stephan Günnemann AI4CE 24 434 0 02 Jun 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