Directional Message Passing for Molecular Graphs

6 March 2020

Stephan Günnemann

Papers citing "Directional Message Passing for Molecular Graphs"

50 / 450 papers shown

Title
DuEqNet: Dual-Equivariance Network in Outdoor 3D Object Detection for Autonomous Driving Xihao Wang Jiaming Lei Hai Lan Arafat Al-Jawari Xian Wei 3DPC 14 6 0 27 Feb 2023
EquiPocket: an E(3)-Equivariant Geometric Graph Neural Network for Ligand Binding Site Prediction Yang Zhang Zhewei Wei Yefei Yuan Zhaohan Ding Wenbing Huang 29 16 0 23 Feb 2023
Data efficiency and extrapolation trends in neural network interatomic potentials Joshua A Vita Daniel Schwalbe-Koda 34 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
Reducing SO(3) Convolutions to SO(2) for Efficient Equivariant GNNs Saro Passaro C. L. Zitnick 3DPC 31 79 0 07 Feb 2023
Linear-scaling kernels for protein sequences and small molecules outperform deep learning while providing uncertainty quantitation and improved interpretability J. Parkinson Wen Wang BDL 19 8 0 07 Feb 2023
GPS++: Reviving the Art of Message Passing for Molecular Property Prediction Dominic Masters Josef Dean Kerstin Klaser Zhiyi Li Sam Maddrell-Mander ... D. Beker Andrew Fitzgibbon Shenyang Huang Ladislav Rampášek Dominique Beaini 30 8 0 06 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
End-to-End Full-Atom Antibody Design Xiangzhe Kong Wenbing Huang Yang Liu 17 48 0 01 Feb 2023
On the Expressive Power of Geometric Graph Neural Networks Chaitanya K. Joshi Cristian Bodnar Simon V. Mathis Taco Cohen Pietro Liò 52 83 0 23 Jan 2023
Spatial Attention Kinetic Networks with E(n)-Equivariance Yuanqing Wang J. Chodera 35 15 0 21 Jan 2023
INO: Invariant Neural Operators for Learning Complex Physical Systems with Momentum Conservation Ning Liu Yue Yu Huaiqian You Neeraj Tatikola AI4CE 15 23 0 29 Dec 2022
Scalable Bayesian Uncertainty Quantification for Neural Network Potentials: Promise and Pitfalls Stephan Thaler Gregor Doehner J. Zavadlav 35 21 0 15 Dec 2022
SchNetPack 2.0: A neural network toolbox for atomistic machine learning Kristof T. Schütt Stefaan S. P. Hessmann Niklas W. A. Gebauer Jonas Lederer M. Gastegger 23 59 0 11 Dec 2022
Integration of Pre-trained Protein Language Models into Geometric Deep Learning Networks Fang Wu Yujun Tao Dragomir R. Radev Jinbo Xu Stan Z. Li AI4CE 30 32 0 07 Dec 2022
Protein Language Models and Structure Prediction: Connection and Progression Bozhen Hu Jun-Xiong Xia Jiangbin Zheng Cheng Tan Yufei Huang Yongjie Xu Stan Z. Li 19 40 0 30 Nov 2022
Coordinating Cross-modal Distillation for Molecular Property Prediction Hao Zhang N. Zhang Ruixin Zhang Lei Shen Yingyi Zhang Meng Liu 20 1 0 30 Nov 2022
Capturing long-range interaction with reciprocal space neural network Hongyu Yu Liangliang Hong Shiyou Chen X. Gong Hongjun Xiang 27 11 0 30 Nov 2022
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
Synthetic data enable experiments in atomistic machine learning John L A Gardner Z. Beaulieu Volker L. Deringer 31 6 0 29 Nov 2022
Invariance-Aware Randomized Smoothing Certificates Jan Schuchardt Stephan Günnemann AAML 28 5 0 25 Nov 2022
BatmanNet: Bi-branch Masked Graph Transformer Autoencoder for Molecular Representation Zhen Wang Zheng Feng Yanjun Li Bowen Li Yongrui Wang C. Sha Min He Xiaolin Li AI4CE 27 9 0 25 Nov 2022
Extreme Acceleration of Graph Neural Network-based Prediction Models for Quantum Chemistry Hatem Helal J. Firoz Jenna A. Bilbrey M. M. Krell Tom Murray Ang Li S. Xantheas Sutanay Choudhury GNN 33 5 0 25 Nov 2022
Learning Regularized Positional Encoding for Molecular Prediction Xiang Gao Weihao Gao Wen Xiao Zhirui Wang Chong Wang Liang Xiang AI4CE 19 1 0 23 Nov 2022
A generalized machine learning framework for brittle crack problems using transfer learning and graph neural networks Roberto Perera V. Agrawal AI4CE 11 9 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
From Node Interaction to Hop Interaction: New Effective and Scalable Graph Learning Paradigm Jie Chen Zilong Li Ying Zhu Junping Zhang Jian Pu 29 8 0 21 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
Equivariant Networks for Crystal Structures Sekouba Kaba Siamak Ravanbakhsh AI4CE 48 23 0 15 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 27 2 0 14 Nov 2022
Deep Surrogate Docking: Accelerating Automated Drug Discovery with Graph Neural Networks Ryien Hosseini F. Simini Austin R. Clyde A. Ramanathan 21 5 0 04 Nov 2022
Geometry-Complete Perceptron Networks for 3D Molecular Graphs Alex Morehead Jianlin Cheng GNN 3DV AI4CE 29 12 0 04 Nov 2022
A 3D-Shape Similarity-based Contrastive Approach to Molecular Representation Learning Austin O. Atsango N. Diamant Ziqing Lu Tommaso Biancalani Gabriele Scalia Kangway V Chuang 24 2 0 03 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 36 19 0 31 Oct 2022
Interpretable Geometric Deep Learning via Learnable Randomness Injection Siqi Miao Yunan Luo Miaoyuan Liu Pan Li 19 25 0 30 Oct 2022
Predicting Protein-Ligand Binding Affinity with Equivariant Line Graph Network Yi Yi Xu Wan Kangfei Zhao Ou-Yang Le Pei-Ying Zhao 21 1 0 27 Oct 2022
Structure-based Drug Design with Equivariant Diffusion Models Arne Schneuing Yuanqi Du Charles Harris Arian R. Jamasb Ilia Igashov ... Pietro Lió Carla P. Gomes Max Welling Michael M. Bronstein B. Correia DiffM 36 194 0 24 Oct 2022
Boosting the Cycle Counting Power of Graph Neural Networks with I $^2$ -GNNs Yinan Huang Xingang Peng Jianzhu Ma Muhan Zhang 84 47 0 22 Oct 2022
A Survey on Graph Counterfactual Explanations: Definitions, Methods, Evaluation, and Research Challenges Mario Alfonso Prado-Romero Bardh Prenkaj Giovanni Stilo F. Giannotti CML 27 30 0 21 Oct 2022
PEMP: Leveraging Physics Properties to Enhance Molecular Property Prediction Yuancheng Sun Yimeng Chen Weizhi Ma Wenhao Huang Kang Liu Zhiming Ma Wei-Ying Ma Yanyan Lan 20 7 0 18 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 30 136 0 13 Oct 2022
Hierarchical Learning in Euclidean Neural Networks Joshua A. Rackers P. Rao 28 1 0 10 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
Machine learning frontier orbital energies of nanodiamonds Thorren Kirschbaum B. V. Seggern J. Dzubiella A. Bande Frank Noé AI4CE 18 3 0 30 Sep 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
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 21 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
Predicting Protein-Ligand Binding Affinity via Joint Global-Local Interaction Modeling Yang Zhang G. Zhou Zhewei Wei Hongteng Xu 27 9 0 18 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