Neural Message Passing for Quantum Chemistry

4 April 2017

Justin Gilmer

Papers citing "Neural Message Passing for Quantum Chemistry"

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Title
Higher-Order Expander Graph Propagation Thomas Christie Yu He 29 3 0 14 Nov 2023
Towards Robotic Tree Manipulation: Leveraging Graph Representations Chung Hee Kim Moonyoung Lee Oliver Kroemer George Kantor 29 5 0 13 Nov 2023
ResMGCN: Residual Message Graph Convolution Network for Fast Biomedical Interactions Discovering Zecheng Yin 29 0 0 13 Nov 2023
Exposition on over-squashing problem on GNNs: Current Methods, Benchmarks and Challenges Dai Shi Andi Han Lequan Lin Yi Guo Junbin Gao 52 13 0 13 Nov 2023
Advancing Drug Discovery with Enhanced Chemical Understanding via Asymmetric Contrastive Multimodal Learning Hao Xu Yifei Wang Yunrui Li Pengyu Hong Pengyu Hong 33 3 0 11 Nov 2023
Multiscale Neural Operators for Solving Time-Independent PDEs Winfried Ripken Lisa Coiffard Felix Pieper Sebastian Dziadzio AI4CE 37 2 0 10 Nov 2023
SIRE: scale-invariant, rotation-equivariant estimation of artery orientations using graph neural networks Dieuwertje Alblas Julian Suk Christoph Brune K. K. Yeung J. Wolterink MedIm 34 4 0 09 Nov 2023
Predicting Properties of Nodes via Community-Aware Features B. Kamiński P. Prałat F. Théberge Sebastian Zajac 48 1 0 08 Nov 2023
Hybrid Focal and Full-Range Attention Based Graph Transformers Minhong Zhu Zhenhao Zhao Weiran Cai 39 0 0 08 Nov 2023
Information-Theoretic Generalization Bounds for Transductive Learning and its Applications Huayi Tang Yong Liu 62 1 0 08 Nov 2023
Learning Robust Multi-Scale Representation for Neural Radiance Fields from Unposed Images Nishant Jain Suryansh Kumar Luc Van Gool 3DV 33 4 0 08 Nov 2023
From Coupled Oscillators to Graph Neural Networks: Reducing Over-smoothing via a Kuramoto Model-based Approach Tuan Nguyen Hirotada Honda Takashi Sano Vinh-Tiep Nguyen Shugo Nakamura Tan-Minh Nguyen 34 4 0 06 Nov 2023
Equivariance Is Not All You Need: Characterizing the Utility of Equivariant Graph Neural Networks for Particle Physics Tasks S. Thais D. Murnane AI4CE 36 4 0 06 Nov 2023
PowerFlowNet: Power Flow Approximation Using Message Passing Graph Neural Networks Nan Lin Stavros Orfanoudakis Nathan Ordonez Cardenas Juan S. Giraldo Pedro P. Vergara 24 8 0 06 Nov 2023
STRIDE: Structure-guided Generation for Inverse Design of Molecules Shehtab Zaman D. Akhiyarov Mauricio Araya-Polo Kenneth Chiu 34 1 0 06 Nov 2023
Edge2Node: Reducing Edge Prediction to Node Classification Zahed Rahmati 7 0 0 06 Nov 2023
GSC: Generalizable Service Coordination Farzad Mohammadi V. Shah-Mansouri GNN 30 1 0 05 Nov 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 29 1 0 05 Nov 2023
KITS: Inductive Spatio-Temporal Kriging with Increment Training Strategy Qianxiong Xu Cheng Long Ziyue Li Sijie Ruan Rui Zhao Zhishuai Li 37 7 0 05 Nov 2023
Sparse Training of Discrete Diffusion Models for Graph Generation Yiming Qin Clément Vignac Pascal Frossard 27 12 0 03 Nov 2023
Neural Atoms: Propagating Long-range Interaction in Molecular Graphs through Efficient Communication Channel Xuan Li Zhanke Zhou Jiangchao Yao Yu Rong Lu Zhang Bo Han 53 3 0 02 Nov 2023
Combating Bilateral Edge Noise for Robust Link Prediction Zhanke Zhou Jiangchao Yao Jiaxu Liu Xiawei Guo Quanming Yao Li He Liang Wang Bo Zheng Bo Han AAML NoLa 28 10 0 02 Nov 2023
$Generating QM1B with PySCF$_{\text{IPU}}$$ Generating QM1B with PySCF $_{\text{IPU}}$ Alexander Mathiasen Hatem Helal Kerstin Klaser Paul Balanca Josef Dean Carlo Luschi Dominique Beaini Andrew Fitzgibbon Dominic Masters 30 1 0 02 Nov 2023
AI for Interpretable Chemistry: Predicting Radical Mechanistic Pathways via Contrastive Learning Mohammadamin Tavakoli Y. T. T. Chiu Alexander Shmakov Ann Marie Carlton David Van Vranken Pierre Baldi 30 2 0 02 Nov 2023
Better Fair than Sorry: Adversarial Missing Data Imputation for Fair GNNs Debolina Halder Lina Arlei Silva 36 0 0 02 Nov 2023
Latent Field Discovery In Interacting Dynamical Systems With Neural Fields Miltiadis Kofinas Erik J. Bekkers N. S. Nagaraja E. Gavves AI4CE 44 7 0 31 Oct 2023
Stochastic Gradient Descent for Gaussian Processes Done Right J. Lin Shreyas Padhy Javier Antorán Austin Tripp Alexander Terenin Csaba Szepesvári José Miguel Hernández-Lobato David Janz 18 8 0 31 Oct 2023
Modeling Dynamics over Meshes with Gauge Equivariant Nonlinear Message Passing Jung Yeon Park Lawson L. S. Wong Robin Walters AI4CE 26 0 0 30 Oct 2023
Prediction of Effective Elastic Moduli of Rocks using Graph Neural Networks Jaehong Chung R. Ahmad WaiChing Sun Wei Cai T. Mukerji 31 8 0 30 Oct 2023
MAG-GNN: Reinforcement Learning Boosted Graph Neural Network Lecheng Kong Jiarui Feng Hao Liu Dacheng Tao Yixin Chen Muhan Zhang AI4CE 37 11 0 29 Oct 2023
Improving Compositional Generalization Using Iterated Learning and Simplicial Embeddings Yi Ren Samuel Lavoie Mikhail Galkin Danica J. Sutherland Aaron Courville 46 15 0 28 Oct 2023
Embedding in Recommender Systems: A Survey Xiangyu Zhao Maolin Wang Xinjian Zhao Jiansheng Li Shucheng Zhou Dawei Yin Qing Li Jiliang Tang Ruocheng Guo AI4TS 38 10 0 28 Oct 2023
The Role of Reference Points in Machine-Learned Atomistic Simulation Models Xiangyun Lei Weike Ye Joseph Montoya Tim Mueller Linda Hung Jens Hummelshoej 18 0 0 28 Oct 2023
Disentangled Representation Learning with Large Language Models for Text-Attributed Graphs Yi Qin Xin Eric Wang Ziwei Zhang Wenwu Zhu AI4CE 22 30 0 27 Oct 2023
Transformers as Graph-to-Graph Models James Henderson Alireza Mohammadshahi Andrei Catalin Coman Lesly Miculicich GNN 35 6 0 27 Oct 2023
Network Design through Graph Neural Networks: Identifying Challenges and Improving Performance Donald Loveland Rajmonda Caceres 27 0 0 26 Oct 2023
Graph Neural Networks with a Distribution of Parametrized Graphs See Hian Lee Feng Ji Kelin Xia Wee Peng Tay 47 0 0 25 Oct 2023
Graph Deep Learning for Time Series Forecasting Andrea Cini Ivan Marisca Daniele Zambon Cesare Alippi AI4TS AI4CE 37 14 0 24 Oct 2023
Density of States Prediction of Crystalline Materials via Prompt-guided Multi-Modal Transformer Namkyeong Lee Heewoong Noh Sungwon Kim Dongmin Hyun Gyoung S. Na Chanyoung Park 34 6 0 24 Oct 2023
Symmetry-preserving graph attention network to solve routing problems at multiple resolutions Cong Dao Tran Thong Bach Truong-Son Hy 39 0 0 24 Oct 2023
ULTRA-DP: Unifying Graph Pre-training with Multi-task Graph Dual Prompt Mouxiang Chen Zemin Liu Chenghao Liu Jundong Li Qiheng Mao Jianling Sun AAML 33 12 0 23 Oct 2023
Rethinking Tokenizer and Decoder in Masked Graph Modeling for Molecules Zhiyuan Liu Yaorui Shi An Zhang Enzhi Zhang Kenji Kawaguchi Xiang Wang Tat-Seng Chua AI4CE 44 36 0 23 Oct 2023
Knowledge-Induced Medicine Prescribing Network for Medication Recommendation A. Mulyadi Heung-Il Suk 45 1 0 23 Oct 2023
Multimodal Graph Learning for Modeling Emerging Pandemics with Big Data Khanh-Tung Tran Truong-Son Hy Lili Jiang Xuan-Son Vu AI4CE 18 2 0 23 Oct 2023
Inferring Relational Potentials in Interacting Systems Armand Comas Massagu´e Yilun Du Christian Fernández S. Ghimire Octavia Camps J. Tenenbaum Mario Sznaier 39 5 0 23 Oct 2023
Can strong structural encoding reduce the importance of Message Passing? Floor Eijkelboom Erik J. Bekkers Michael M. Bronstein Francesco Di Giovanni University of Amsterdam 27 2 0 22 Oct 2023
Learning Invariant Molecular Representation in Latent Discrete Space Zhuang Xiang Qiang Zhang Keyan Ding Yatao Bian Xiao Wang Jingsong Lv Hongyang Chen Huajun Chen OOD 40 16 0 22 Oct 2023
Ensemble Learning for Graph Neural Networks Zhen Hao Wong Ling Yue Quanming Yao 54 0 0 22 Oct 2023
Graph Neural Networks and Applied Linear Algebra Nicholas S. Moore Eric C. Cyr Peter Ohm C. Siefert R. Tuminaro 35 4 0 21 Oct 2023
Learning Interatomic Potentials at Multiple Scales Xiang Fu Albert Musaelian Anders Johansson Tommi Jaakkola Boris Kozinsky 34 2 0 20 Oct 2023