Neural Message Passing for Quantum Chemistry

4 April 2017

Justin Gilmer

Papers citing "Neural Message Passing for Quantum Chemistry"

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Title
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Generalization Limits of Graph Neural Networks in Identity Effects Learning Giuseppe Alessio D’Inverno Simone Brugiapaglia Mirco Ravanelli 44 3 0 30 Jun 2023
Why Deep Models Often cannot Beat Non-deep Counterparts on Molecular Property Prediction? Jun Xia Lecheng Zhang Xiao Zhu Stan Z. Li 61 3 0 30 Jun 2023
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Individual and Structural Graph Information Bottlenecks for Out-of-Distribution Generalization Ling Yang Jiayi Zheng Heyuan Wang Zhongyi Liu Zhilin Huang Shenda Hong Wentao Zhang Tengjiao Wang 44 13 0 28 Jun 2023
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Physics-inspired spatiotemporal-graph AI ensemble for the detection of higher order wave mode signals of spinning binary black hole mergers Minyang Tian Eliu A. Huerta Huihuo Zheng Prayush Kumar 23 5 0 27 Jun 2023
Asynchronous Algorithmic Alignment with Cocycles Andrew Dudzik Tamara von Glehn Razvan Pascanu Petar Velivcković 44 9 0 27 Jun 2023
Tanimoto Random Features for Scalable Molecular Machine Learning Austin Tripp S. Bacallado Sukriti Singh José Miguel Hernández-Lobato 34 7 0 26 Jun 2023
Interpretable Sparsification of Brain Graphs: Better Practices and Effective Designs for Graph Neural Networks Gao Li M. Duda Xinming Zhang Danai Koutra Yujun Yan 52 8 0 26 Jun 2023
A Survey on Graph Neural Network Acceleration: Algorithms, Systems, and Customized Hardware Shichang Zhang Atefeh Sohrabizadeh Cheng Wan Zijie Huang Ziniu Hu Yewen Wang Yingyan Lin Lin Jason Cong Yizhou Sun GNN AI4CE 46 24 0 24 Jun 2023
Graph Neural Networks Provably Benefit from Structural Information: A Feature Learning Perspective Wei Huang Yuanbin Cao Hong Wang Xin Cao Taiji Suzuki MLT 45 7 0 24 Jun 2023
Curvature-enhanced Graph Convolutional Network for Biomolecular Interaction Prediction Cong Shen Pingjian Ding Junjie Wee Jialin Bi Jiawei Luo Kelin Xia GNN 43 6 0 23 Jun 2023
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Evolving Computation Graphs Andreea Deac Jian Tang 46 1 0 22 Jun 2023
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Graph Self-Supervised Learning for Endoscopic Image Matching Manel Farhat A. Ben-Hamadou SSL 31 1 0 19 Jun 2023
P-tensors: a General Formalism for Constructing Higher Order Message Passing Networks Tianyi Sun Andrew R. Hands Risi Kondor 32 2 0 19 Jun 2023
Bkd-FedGNN: A Benchmark for Classification Backdoor Attacks on Federated Graph Neural Network Fan Liu Siqi Lai Yansong Ning Hao Liu AAML FedML 50 3 0 17 Jun 2023
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On the Interplay of Subset Selection and Informed Graph Neural Networks Niklas Breustedt Paolo Climaco Jochen Garcke J. Hamaekers Gitta Kutyniok D. Lorenz Rick Oerder Chirag Varun Shukla 38 0 0 15 Jun 2023
Symmetry-Informed Geometric Representation for Molecules, Proteins, and Crystalline Materials Shengchao Liu Weitao Du Yanjing Li Zhuoxinran Li Zhiling Zheng ... Anima Anandkumar C. Borgs J. Chayes Hongyu Guo Jian Tang AI4CE 38 20 0 15 Jun 2023
MUBen: Benchmarking the Uncertainty of Molecular Representation Models Yinghao Li Lingkai Kong Yuanqi Du Yue Yu Yuchen Zhuang Wenhao Mu Chao Zhang 40 9 0 14 Jun 2023
Self-supervised Learning and Graph Classification under Heterophily Y. Ding Ziqiang Liu Hao Hao SSL 28 1 0 14 Jun 2023
Graph Structure and Feature Extrapolation for Out-of-Distribution Generalization Xiner Li Shurui Gui Youzhi Luo Shuiwang Ji OODD OOD 44 10 0 13 Jun 2023
Automated 3D Pre-Training for Molecular Property Prediction Xu Wang Huan Zhao Weiwei Tu Quanming Yao AI4CE 36 35 0 13 Jun 2023
A Graph Transformer-Driven Approach for Network Robustness Learning Yu Zhang Jia Li Jie Ding Xiang Li OOD AAML OffRL 21 3 0 12 Jun 2023
Efficient Approximations of Complete Interatomic Potentials for Crystal Property Prediction Yu-Ching Lin Keqiang Yan Youzhi Luo Yi Liu Xiaoning Qian Shuiwang Ji 76 34 0 12 Jun 2023
Finding Hamiltonian cycles with graph neural networks Filip Bosnić M. Šikić 35 1 0 10 Jun 2023
TensorNet: Cartesian Tensor Representations for Efficient Learning of Molecular Potentials Guillem Simeon Gianni De Fabritiis 40 45 0 10 Jun 2023
Any-dimensional equivariant neural networks Eitan Levin Mateo Díaz 39 7 0 10 Jun 2023
Path Neural Networks: Expressive and Accurate Graph Neural Networks Gaspard Michel Giannis Nikolentzos J. Lutzeyer Michalis Vazirgiannis GNN 31 27 0 09 Jun 2023
CrysMMNet: Multimodal Representation for Crystal Property Prediction Kishalay Das Pawan Goyal Seung-Cheol Lee S. Bhattacharjee Niloy Ganguly 23 12 0 09 Jun 2023
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Simplicial Message Passing for Chemical Property Prediction Hai Lan Xian Wei 30 0 0 09 Jun 2023
Comprehensive evaluation of deep and graph learning on drug-drug interactions prediction Xuan Lin Lichang Dai Yafang Zhou Zunpeng Yu Wen Zhang ... Li Zeng Hao-Heng Chen Bosheng Song Philip S. Yu Xiangxiang Zeng GNN 31 57 0 08 Jun 2023
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Efficient and Equivariant Graph Networks for Predicting Quantum Hamiltonian Haiyang Yu Zhao Xu X. Qian Xiaoning Qian Shuiwang Ji 47 25 0 08 Jun 2023
Multi-task Bioassay Pre-training for Protein-ligand Binding Affinity Prediction Jiaxian Yan Zhaofeng Ye Ziyi Yang Chengqiang Lu Shengyu Zhang Qi Liu J. Qiu 48 11 0 08 Jun 2023
XInsight: Revealing Model Insights for GNNs with Flow-based Explanations Eli J. Laird Ayesh Madushanka E. Kraka Corey Clark 37 1 0 07 Jun 2023
Limits, approximation and size transferability for GNNs on sparse graphs via graphops Thien Le Stefanie Jegelka 40 10 0 07 Jun 2023
Neural Embeddings for Protein Graphs Francesco Ceccarelli Lorenzo Giusti S. Holden Pietro Lio 32 0 0 07 Jun 2023
Retrosynthesis Prediction with Local Template Retrieval Shufang Xie Rui Yan Junliang Guo Yingce Xia Lijun Wu Tao Qin 36 13 0 07 Jun 2023