GemNet: Universal Directional Graph Neural Networks for Molecules

2 June 2021

Stephan Günnemann

Papers citing "GemNet: Universal Directional Graph Neural Networks for Molecules"

50 / 237 papers shown

Title
Data efficiency and extrapolation trends in neural network interatomic potentials Joshua A Vita Daniel Schwalbe-Koda 36 16 0 12 Feb 2023
Is Distance Matrix Enough for Geometric Deep Learning? Zian Li Xiyuan Wang Yinan Huang Muhan Zhang 37 17 0 11 Feb 2023
Attending to Graph Transformers Luis Muller Mikhail Galkin Christopher Morris Ladislav Rampášek 49 86 0 08 Feb 2023
Generalizing Neural Wave Functions Nicholas Gao Stephan Günnemann 21 20 0 08 Feb 2023
Reducing SO(3) Convolutions to SO(2) for Efficient Equivariant GNNs Saro Passaro C. L. Zitnick 3DPC 34 79 0 07 Feb 2023
Learning a Fourier Transform for Linear Relative Positional Encodings in Transformers K. Choromanski Shanda Li Valerii Likhosherstov Kumar Avinava Dubey Shengjie Luo Di He Yiming Yang Tamás Sarlós Thomas Weingarten Adrian Weller 37 8 0 03 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
Equivariant Message Passing Neural Network for Crystal Material Discovery Astrid Klipfel Olivier Peltre Najwa Harrati Yael Fregier A. Sayede Zied Bouraoui 16 9 0 01 Feb 2023
Complete Neural Networks for Complete Euclidean Graphs Snir Hordan Tal Amir S. Gortler Nadav Dym 3DPC 29 5 0 31 Jan 2023
On the Expressive Power of Geometric Graph Neural Networks Chaitanya K. Joshi Cristian Bodnar Simon V. Mathis Taco Cohen Pietro Liò 55 83 0 23 Jan 2023
Spatial Attention Kinetic Networks with E(n)-Equivariance Yuanqing Wang J. Chodera 35 15 0 21 Jan 2023
State of the Art and Potentialities of Graph-level Learning Zhenyu Yang Ge Zhang Jia Wu Jian Yang Quan.Z Sheng ... Charu C. Aggarwal Hao Peng Wenbin Hu Edwin R. Hancock Pietro Lio' GNN AI4CE 35 10 0 14 Jan 2023
QESK: Quantum-based Entropic Subtree Kernels for Graph Classification Lu Bai Lixin Cui Edwin R. Hancock 40 0 0 10 Dec 2022
Capturing long-range interaction with reciprocal space neural network Hongyu Yu Liangliang Hong Shiyou Chen X. Gong Hongjun Xiang 29 11 0 30 Nov 2022
Invariance-Aware Randomized Smoothing Certificates Jan Schuchardt Stephan Günnemann AAML 28 5 0 25 Nov 2022
An ensemble of VisNet, Transformer-M, and pretraining models for molecular property prediction in OGB Large-Scale Challenge @ NeurIPS 2022 Yusong Wang Shaoning Li Zun Wang Xinheng He Bin Shao Tie-Yan Liu Tong Wang AI4CE 20 4 0 23 Nov 2022
Learning Regularized Positional Encoding for Molecular Prediction Xiang Gao Weihao Gao Wen Xiao Zhirui Wang Chong Wang Liang Xiang AI4CE 27 1 0 23 Nov 2022
Supervised Pretraining for Molecular Force Fields and Properties Prediction Xiang Gao Weihao Gao Wen Xiao Zhirui Wang Chong Wang Liang Xiang AI4CE 20 8 0 23 Nov 2022
Where Will Players Move Next? Dynamic Graphs and Hierarchical Fusion for Movement Forecasting in Badminton Kai-Shiang Chang Wei-Yao Wang Wen-Chih Peng AI4TS 31 14 0 22 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
Fast Uncertainty Estimates in Deep Learning Interatomic Potentials Albert J. W. Zhu Simon L. Batzner Albert Musaelian Boris Kozinsky 22 45 0 17 Nov 2022
ParticleGrid: Enabling Deep Learning using 3D Representation of Materials Shehtab Zaman E. Ferguson Cécile Pereira D. Akhiyarov Mauricio Araya-Polo Kenneth Chiu DiffM AI4CE 21 2 0 15 Nov 2022
Graph Contrastive Learning with Implicit Augmentations Huidong Liang Xingjian Du Bilei Zhu Zejun Ma Ke Chen Junbin Gao 19 29 0 07 Nov 2022
Learning the shape of protein micro-environments with a holographic convolutional neural network Michael N. Pun Andrew Ivanov Quinn Bellamy Zachary Montague Colin H. LaMont P. Bradley J. Otwinowski Armita Nourmohammad 16 12 0 05 Nov 2022
HAQJSK: Hierarchical-Aligned Quantum Jensen-Shannon Kernels for Graph Classification Lu Bai Lixin Cui Yue Wang Ming Li Edwin R. Hancock 19 41 0 05 Nov 2022
Geometry-Complete Perceptron Networks for 3D Molecular Graphs Alex Morehead Jianlin Cheng GNN 3DV AI4CE 29 12 0 04 Nov 2022
The Open MatSci ML Toolkit: A Flexible Framework for Machine Learning in Materials Science Santiago Miret Kin Long Kelvin Lee Carmelo Gonzales Marcel Nassar Matthew Spellings 38 19 0 31 Oct 2022
Injecting Domain Knowledge from Empirical Interatomic Potentials to Neural Networks for Predicting Material Properties Zeren Shui Daniel S. Karls Mingjian Wen Ilia Nikiforov E. Tadmor George Karypis 46 7 0 14 Oct 2022
Forces are not Enough: Benchmark and Critical Evaluation for Machine Learning Force Fields with Molecular Simulations Xiang Fu Zhenghao Wu Wujie Wang T. Xie S. Keten Rafael Gómez-Bombarelli Tommi Jaakkola 32 136 0 13 Oct 2022
Hyperactive Learning (HAL) for Data-Driven Interatomic Potentials Cas van der Oord Matthias Sachs D. P. Kovács Christoph Ortner Gábor Csányi 41 64 0 09 Oct 2022
Improving Molecular Pretraining with Complementary Featurizations Yanqiao Zhu Dingshuo Chen Yuanqi Du Yingze Wang Qiang Liu Shu Wu AI4CE 36 6 0 29 Sep 2022
Machine learning and invariant theory Ben Blum-Smith Soledad Villar AI4CE 36 16 0 29 Sep 2022
Learned Force Fields Are Ready For Ground State Catalyst Discovery Michael Schaarschmidt M. Rivière A. Ganose J. Spencer Alex Gaunt J. Kirkpatrick Simon Axelrod Peter W. Battaglia Jonathan Godwin 23 10 0 26 Sep 2022
Periodic Graph Transformers for Crystal Material Property Prediction Keqiang Yan Yi Liu Yu-Ching Lin Shuiwang Ji AI4TS 88 84 0 23 Sep 2022
Multi-Task Mixture Density Graph Neural Networks for Predicting Cu-based Single-Atom Alloy Catalysts for CO2 Reduction Reaction Chen Liang Bo-Lan Wang Shaogang Hao Guangyong Chen Pheng-Ann Heng Xiaolong Zou 50 1 0 15 Sep 2022
Graph Neural Networks for Molecules Yuyang Wang Zijie Li A. Farimani GNN AI4CE 45 20 0 12 Sep 2022
Domain-informed graph neural networks: a quantum chemistry case study Jay Morgan A. Paiement C. Klinke GNN 32 4 0 25 Aug 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 37 37 0 17 Aug 2022
Graph neural networks for materials science and chemistry Patrick Reiser Marlen Neubert André Eberhard Luca Torresi Chen Zhou ... Houssam Metni Clint van Hoesel Henrik Schopmans T. Sommer Pascal Friederich GNN AI4CE 50 373 0 05 Aug 2022
Graph Neural Network with Local Frame for Molecular Potential Energy Surface Xiyuan Wang Muhan Zhang 38 9 0 01 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
Graph-based Molecular Representation Learning Zhichun Guo Kehan Guo B. Nan Yijun Tian Roshni G. Iyer ... Olaf Wiest Xiangliang Zhang Wei Wang Chuxu Zhang Nitesh V. Chawla AI4CE 22 60 0 08 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 83 216 0 23 Jun 2022
Ordered Subgraph Aggregation Networks Chao Qian Gaurav Rattan Floris Geerts Christopher Morris Mathias Niepert 41 57 0 22 Jun 2022
Cluster Generation via Deep Energy-Based Model A. Y. Artsukevich S. Lepeshkin 29 0 0 17 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 28 173 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 41 89 0 17 Jun 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 44 441 0 15 Jun 2022