Graph Neural Networks

ICML 2024arXiv:2402.08170

#2

LLaGA: Large Language and Graph Assistant

Runjin Chen, Tong Zhao, Ajay Jaiswal et al.

graph neural networkslarge language modelsgraph-structured datastructure-aware sequences+2

148

AAAI 2024arXiv:2309.05305

#3

Fully-Connected Spatial-Temporal Graph for Multivariate Time-Series Data

Yucheng Wang, Yuecong Xu, Jianfei Yang et al.

multivariate time-series dataspatial-temporal dependenciesgraph neural networkssensor correlation modeling+4

104

ICLR 2024arXiv:2310.04668

#4

Label-free Node Classification on Graphs with Large Language Models (LLMs)

Zhikai Chen, Haitao Mao, Hongzhi Wen et al.

95

ICML 2024arXiv:2402.02216

#5

Position: Graph Foundation Models Are Already Here

Haitao Mao, Zhikai Chen, Wenzhuo Tang et al.

graph foundation modelsgraph vocabularygraph neural networkspositive transfer+4

79

AAAI 2024arXiv:2312.06441

#6

Revisiting Graph-Based Fraud Detection in Sight of Heterophily and Spectrum

Fan Xu, Nan Wang, Hao Wu et al.

graph-based fraud detectionheterophilic graphsgraph neural networksspectral graph analysis+2

58

ICLR 2024arXiv:2403.12143

#7

Graph Neural Networks for Learning Equivariant Representations of Neural Networks

Miltiadis (Miltos) Kofinas, Boris Knyazev, Yan Zhang et al.

53

ICML 2024arXiv:2310.01267

#8

Cooperative Graph Neural Networks

Ben Finkelshtein, Xingyue Huang, Michael Bronstein et al.

graph neural networksmessage-passing paradigmnode representation learningdynamic message-passing+2

52

ICLR 2024arXiv:2312.04501

#9

Dynamic Semantic-Based Spatial Graph Convolution Network for Skeleton-Based Human Action Recognition

Jianyang Xie, Yanda Meng, Yitian Zhao et al.

Graph Metanetworks for Processing Diverse Neural Architectures

Derek Lim, Haggai Maron, Marc T Law et al.

45

ICML 2024arXiv:2202.13060

#11

Graph Attention Retrospective

Kimon Fountoulakis, Amit Levi, Shenghao Yang et al.

graph attention networksnode classificationstochastic block modelmixture of gaussians+3

43

ICLR 2024arXiv:2403.16030

#12

VCR-Graphormer: A Mini-batch Graph Transformer via Virtual Connections

Dongqi Fu, Zhigang Hua, Yan Xie et al.

41

ICML 2024arXiv:2405.04773

#13

Hypergraph-enhanced Dual Semi-supervised Graph Classification

Wei Ju, Zhengyang Mao, Siyu Yi et al.

semi-supervised graph classificationgraph neural networkshypergraph structure learninghigher-order dependencies+3

38

ICLR 2024arXiv:2412.00020

#14

Robust Node Classification on Graph Data with Graph and Label Noise

Yonghua Zhu, Lei Feng, Zhenyun Deng et al.

Partitioning Message Passing for Graph Fraud Detection

Wei Zhuo, Zemin Liu, Bryan Hooi et al.

37

ICLR 2024arXiv:2308.02117

#16

VQGraph: Rethinking Graph Representation Space for Bridging GNNs and MLPs

Ling Yang, Ye Tian, Minkai Xu et al.

36

ICLR 2024arXiv:2310.00793

#17

Revisiting Link Prediction: a data perspective

Haitao Mao, Juanhui Li, Harry Shomer et al.

35

AAAI 2024arXiv:2312.12697

#18

DGCLUSTER: A Neural Framework for Attributed Graph Clustering via Modularity Maximization

Aritra Bhowmick, Mert Kosan, Zexi Huang et al.

graph clusteringmodularity maximizationgraph neural networksattributed graphs+3

34

NEURIPS 2025arXiv:2502.10818

#19

On Vanishing Gradients, Over-Smoothing, and Over-Squashing in GNNs: Bridging Recurrent and Graph Learning

Alvaro Arroyo, Alessio Gravina, Benjamin Gutteridge et al.

34

AAAI 2024arXiv:2403.12474

#20

FairSIN: Achieving Fairness in Graph Neural Networks through Sensitive Information Neutralization

Cheng Yang, Jixi Liu, Yunhe Yan et al.

graph neural networksfairness in gnnssensitive information neutralizationbias mitigation+3

33

AAAI 2024arXiv:2312.10988

#21

Graph Invariant Learning with Subgraph Co-mixup for Out-of-Distribution Generalization

Tianrui Jia, Haoyang Li, Cheng Yang et al.

graph invariant learningout-of-distribution generalizationsubgraph extractionenvironment mixup+4

33

AAAI 2024arXiv:2306.11586

#22

Provably Powerful Graph Neural Networks for Directed Multigraphs

Beni Egressy, Luc von Niederhäusern, Jovan Blanuša et al.

graph neural networksdirected multigraphssubgraph detectionmessage passing+3

33

CVPR 2024arXiv:2405.06849

#23

GreedyViG: Dynamic Axial Graph Construction for Efficient Vision GNNs

Mustafa Munir, William Avery, Md Mostafijur Rahman et al.

vision graph neural networksgraph construction efficiencydynamic axial graphhybrid cnn-gnn architecture+4

32

AAAI 2024arXiv:2402.16012

#24

Deep Contrastive Graph Learning with Clustering-Oriented Guidance

Mulin Chen, Bocheng Wang, Xuelong Li

graph convolutional networksgraph-based clusteringcontrastive learningauto-encoder architecture+4

31

ICLR 2024arXiv:2308.13212

#25

SEGNO: Generalizing Equivariant Graph Neural Networks with Physical Inductive Biases

Yang Liu, Jiashun Cheng, Haihong Zhao et al.

31

AAAI 2024arXiv:2309.12971

#26

Higher-Order Graph Convolutional Network with Flower-Petals Laplacians on Simplicial Complexes

Yiming Huang, Yujie Zeng, Qiang Wu et al.

graph neural networkssimplicial complexeshigher-order interactionsgraph convolutional network+3

29

AAAI 2024arXiv:2312.08616

#27

A Generalized Neural Diffusion Framework on Graphs

10011 Yibo Li, Xiao Wang, Hongrui Liu et al.

graph neural networksdiffusion processgraph diffusion networkshigh-order diffusion equation+3

29

AAAI 2024arXiv:2312.11143

#28

Learning Domain-Independent Heuristics for Grounded and Lifted Planning

28

ICLR 2024arXiv:2312.11529

#29

DREAM: Dual Structured Exploration with Mixup for Open-set Graph Domain Adaption

Nan Yin, Mengzhu Wang, Mengzhu Wang et al.

Efficient and Scalable Graph Generation through Iterative Local Expansion

Andreas Bergmeister, Karolis Martinkus, Nathanaël Perraudin et al.

ICML 2024arXiv:2402.01107

#31

Simulation of Graph Algorithms with Looped Transformers

Artur Back de Luca, Kimon Fountoulakis

graph algorithm simulationlooped transformerstransformer networksrelational data reasoning+4

AAAI 2024arXiv:2401.01232

#32

Motif-Aware Riemannian Graph Neural Network with Generative-Contrastive Learning

Li Sun, Zhenhao Huang, Zixi Wang et al.

riemannian graph representationdiverse-curvature manifoldmotif regularitygraph neural network+4

ICML 2024arXiv:2309.04332

#33

Graph Neural Networks Use Graphs When They Shouldn't

Maya Bechler-Speicher, Ido Amos, Ran Gilad-Bachrach et al.

graph neural networksgraph overfittingimplicit biasgradient descent learning+3

ICLR 2024arXiv:2310.02156

#34

Probabilistically Rewired Message-Passing Neural Networks

Chendi Qian, Andrei Manolache, Kareem Ahmed et al.

26

AAAI 2024arXiv:2312.13032

#35

NodeMixup: Tackling Under-Reaching for Graph Neural Networks

Weigang Lu, Ziyu Guan, Wei Zhao et al.

graph neural networkssemi-supervised node classificationunder-reaching issuelabeled-unlabeled pairs mixup+2

24

AAAI 2024arXiv:2308.09517

#36

Transitivity-Preserving Graph Representation Learning for Bridging Local Connectivity and Role-Based Similarity

Van Thuy Hoang, O-Joun Lee

24

ICLR 2025arXiv:2406.02997

#37

Learning to Reweight for Generalizable Graph Neural Network

Zhengyu Chen, Teng Xiao, Kun Kuang et al.

Residual Connections and Normalization Can Provably Prevent Oversmoothing in GNNs

Michael Scholkemper, Xinyi Wu, Ali Jadbabaie et al.

graph neural networksoversmoothing problemresidual connectionsnormalization layers+4

23

AAAI 2024arXiv:2307.16092

#39

Feature Transportation Improves Graph Neural Networks

Moshe Eliasof, Eldad Haber, Eran Treister

22

AAAI 2024arXiv:2312.11850

#40

GCNext: Towards the Unity of Graph Convolutions for Human Motion Prediction

Xinshun Wang, Qiongjie Cui, Chen Chen et al.

graph convolutional networkshuman motion predictionuniversal graph convolutiondynamic graph convolutions+3

22

AAAI 2024arXiv:2401.06176

#41

GOODAT: Towards Test-Time Graph Out-of-Distribution Detection

Luzhi Wang, Di Jin, He Zhang et al.

graph out-of-distribution detectiontest-time adaptationgraph neural networksunsupervised learning+4

21

ICLR 2024arXiv:2310.02232

#42

HoloNets: Spectral Convolutions do extend to Directed Graphs

Christian Koke, Daniel Cremers

21

ICLR 2025arXiv:2504.02843

#43

Learning Distributions of Complex Fluid Simulations with Diffusion Graph Networks

Mario Lino, Tobias Pfaff, Nils Thuerey

diffusion graph networkslatent-space diffusion modelinggraph-based latent diffusionunstructured mesh operations+4

21

ICLR 2025arXiv:2405.15429

#44

E(n) Equivariant Topological Neural Networks

Claudio Battiloro, Ege Karaismailoglu, Mauricio Tec et al.

equivariant message-passingtopological deep learningcombinatorial complexesgeometric graph networks+4

AAAI 2024arXiv:2401.02682

#45

Homophily-Related: Adaptive Hybrid Graph Filter for Multi-View Graph Clustering

Zichen Wen, Yawen Ling, Yazhou Ren et al.

ICML 2024arXiv:2402.10634

#46

Graph-based Forecasting with Missing Data through Spatiotemporal Downsampling

Ivan Marisca, Cesare Alippi, Filippo Maria Bianchi

spatiotemporal forecastinggraph neural networksmissing data imputationhierarchical downsampling+3

ICLR 2025arXiv:2406.03386

#47

Learning Long Range Dependencies on Graphs via Random Walks

Dexiong Chen, Till Schulz, Karsten Borgwardt

graph neural networkslong-range dependenciesrandom walk sequencesgraph transformers+3

ICML 2024arXiv:2402.08595

#48

Homomorphism Counts for Graph Neural Networks: All About That Basis

Emily Jin, Michael Bronstein, Ismail Ceylan et al.

homomorphism countsgraph neural networksexpressive powersubgraph pattern counts+3

ICML 2024arXiv:2311.01198

#49

Gaussian Processes on Cellular Complexes

Mathieu Alain, So Takao, Brooks Paige et al.

gaussian processescellular complexesgraph kernelstopological inductive biases+3

ICML 2024arXiv:2405.11801

#50

LSEnet: Lorentz Structural Entropy Neural Network for Deep Graph Clustering

Li Sun, Zhenhao Huang, Hao Peng et al.

graph clusteringstructural information theorydifferentiable structural informationhyperbolic space models+4

AAAI 2024arXiv:2312.13583

#51

Fine-Tuning Graph Neural Networks by Preserving Graph Generative Patterns

Yifei Sun, Qi Zhu, Yang Yang et al.

graph neural networkspre-training fine-tuninggraph generative patternsgraphon reconstruction+3

ICML 2024arXiv:2406.01977

#52

What Improves the Generalization of Graph Transformers? A Theoretical Dive into the Self-attention and Positional Encoding

Hongkang Li, Meng Wang, Tengfei Ma et al.

graph transformersself-attention mechanismpositional encodingsemi-supervised node classification+3

ICML 2024arXiv:2407.11083

#53

Empowering Graph Invariance Learning with Deep Spurious Infomax

Tianjun Yao, Yongqiang Chen, Zhenhao Chen et al.

graph invariance learningout-of-distribution generalizationspurious featuresinfomax principle+2

ICLR 2024arXiv:2310.20082

#54

Efficient Subgraph GNNs by Learning Effective Selection Policies

Beatrice Bevilacqua, Moshe Eliasof, Eli Meirom et al.

AAAI 2024arXiv:2401.02610

#55

DHGCN: Dynamic Hop Graph Convolution Network for Self-Supervised Point Cloud Learning

Jincen Jiang, Lizhi Zhao, Xuequan Lu et al.

ICML 2024arXiv:2406.03193

#56

Graph Neural Network Explanations are Fragile

Jiate Li, Meng Pang, Yun Dong et al.

graph neural networksexplainable aiadversarial attacksgraph structure perturbation+2

ICML 2024arXiv:2406.04336

#57

On the Expressive Power of Spectral Invariant Graph Neural Networks

Bohang Zhang, Lingxiao Zhao, Haggai Maron

spectral invariant architecturesgraph neural networksexpressive power analysiseigenspace projection+4

ICML 2024arXiv:2401.09125

#58

Understanding Heterophily for Graph Neural Networks

Junfu Wang, Yuanfang Guo, Liang Yang et al.

graph neural networksheterophily patternsstochastic block modelsgraph convolution operations+3

NEURIPS 2025arXiv:2504.00711

#59

GraphMaster: Automated Graph Synthesis via LLM Agents in Data-Limited Environments

Enjun Du, Xunkai Li, Tian Jin et al.

graph foundation modelsgraph data synthesisllm agentssemantic coherence+4

ICLR 2025arXiv:2502.01122

#60

Learning Efficient Positional Encodings with Graph Neural Networks

Charilaos Kanatsoulis, Evelyn Choi, Stefanie Jegelka et al.

positional encodingsgraph neural networkspermutation equivariancemessage-passing operations+4

ICML 2024arXiv:2312.06581

#61

Grokking Group Multiplication with Cosets

Dashiell Stander, Qinan Yu, Honglu Fan et al.

neural network interpretabilityalgorithmic taskspermutation groupssubgroup structure+4

ICLR 2025arXiv:2405.14260

#62

Graph Sparsification via Mixture of Graphs

Guibin Zhang, Xiangguo SUN, Yanwei Yue et al.

graph sparsificationgraph neural networksmixture of expertsgrassmann manifold+4

AAAI 2024arXiv:2312.05596

#63

SURER: Structure-Adaptive Unified Graph Neural Network for Multi-View Clustering

Jing Wang, Songhe Feng, Gengyu Lyu et al.

Factorized Explainer for Graph Neural Networks

16

ICML 2025arXiv:2502.06784

#65

RelGNN: Composite Message Passing for Relational Deep Learning

Tianlang Chen, Charilaos Kanatsoulis, Jure Leskovec

relational deep learninggraph neural networkscomposite message passingrelational databases+3

16

ICML 2025arXiv:2501.18739

#66

Hypergraph Joint Representation Learning for Hypervertices and Hyperedges via Cross Expansion

Yuguang Yan, Yuanlin Chen, Shibo Wang et al.

Beyond Message Passing: Neural Graph Pattern Machine

Zehong Wang, Zheyuan Zhang, Tianyi MA et al.

ICML 2024arXiv:2406.07955

#68

How Interpretable Are Interpretable Graph Neural Networks?

Yongqiang Chen, Yatao Bian, Bo Han et al.

interpretable graph neural networksattention-based mechanismsubgraph multilinear extensiongraph classification benchmarks+2

ICML 2024arXiv:2310.09202

#69

Graph Distillation with Eigenbasis Matching

Yang Liu, Deyu Bo, Chuan Shi

graph distillationspectral approximationgraph neural networkseigenbasis matching+2

AAAI 2024arXiv:2312.11198

#70

Signed Graph Neural Ordinary Differential Equation for Modeling Continuous-Time Dynamics

Lanlan Chen, Kai Wu, Jian Lou et al.

signed graph neural networkscontinuous-time dynamicsordinary differential equationsgraph neural controlled differential equations+3

ICLR 2024arXiv:2401.14578

#71

GOAt: Explaining Graph Neural Networks via Graph Output Attribution

Shengyao Lu, Keith G Mills, Jiao He et al.

ICLR 2024arXiv:2310.04612

#72

Structural Information Enhanced Graph Representation for Link Prediction

Lei Shi, Bin Hu, Deng Zhao et al.

A Topological Perspective on Demystifying GNN-Based Link Prediction Performance

Yu Wang, Tong Zhao, Yuying Zhao et al.

ICML 2024arXiv:2405.16183

#74

Graph Neural PDE Solvers with Conservation and Similarity-Equivariance

Masanobu Horie, NAOTO MITSUME

graph neural networkspartial differential equationsconservation lawsphysical symmetries+3

3d equivariant gnnsgeometric tensor networksmolecular property predictioneuclidean group equivariance+4

#75

Tensorized Label Learning on Anchor Graph

Jing Li, Quanxue Gao, Qianqian Wang et al.

GotenNet: Rethinking Efficient 3D Equivariant Graph Neural Networks

Sarp Aykent, Tian Xia

ICLR 2025

ICLR 2024arXiv:2312.08515

#77

Simplicial Representation Learning with Neural $k$-Forms

Kelly Maggs, Celia Hacker, Bastian Rieck

ICLR 2025arXiv:2502.05780

#78

GOLD: Graph Out-of-Distribution Detection via Implicit Adversarial Latent Generation

Danny Wang, Ruihong Qiu, Guangdong Bai et al.

AAAI 2024arXiv:2402.12946

#79

A Twist for Graph Classification: Optimizing Causal Information Flow in Graph Neural Networks

Zhe Zhao, Pengkun Wang, HaiBin Wen et al.

Cell Graph Transformer for Nuclei Classification

Wei Lou, Guanbin Li, Xiang Wan et al.

cell graph transformernuclei classificationhistopathology imagesgraph neural networks+4

AAAI 2025arXiv:2412.12984

#81

Cluster-guided Contrastive Class-imbalanced Graph Classification

Wei Ju, Zhengyang Mao, Siyu Yi et al.

ICLR 2025arXiv:2405.20445

#82

Fully-inductive Node Classification on Arbitrary Graphs

Jianan Zhao, Zhaocheng Zhu, Mikhail Galkin et al.

node classificationgraph machine learninginductive learninglineargnn+3

CVPR 2024arXiv:2308.15984

#83

Learning Structure-from-Motion with Graph Attention Networks

Lucas Brynte, José Pedro Iglesias, Carl Olsson et al.

ICML 2024arXiv:2402.01242

#84

Two Heads Are Better Than One: Boosting Graph Sparse Training via Semantic and Topological Awareness

Guibin Zhang, Yanwei Yue, kun wang et al.

graph neural networksgraph sparse trainingsparse graph optimizationtopological information preservation+4

AAAI 2024arXiv:2312.05736

#85

ASWT-SGNN: Adaptive Spectral Wavelet Transform-Based Self-Supervised Graph Neural Network

Ruyue Liu, Rong Yin, Yong Liu et al.

AAAI 2025arXiv:2501.10459

#86

Efficient Traffic Prediction Through Spatio-Temporal Distillation

Qianru Zhang, Xinyi Gao, Haixin Wang et al.

ICML 2024arXiv:2402.13937

#87

Verifying message-passing neural networks via topology-based bounds tightening

Christopher Hojny, Shiqiang Zhang, Juan Campos et al.

message-passing neural networksrobustness verificationmixed-integer optimizationtopological perturbations+4

ICLR 2024arXiv:2404.17947

#88

Bounding the Expected Robustness of Graph Neural Networks Subject to Node Feature Attacks

Yassine ABBAHADDOU, Sofiane ENNADIR, Johannes Lutzeyer et al.

ICML 2025arXiv:2406.05225

#89

HONGAT: Graph Attention Networks in the Presence of High-Order Neighbors

Heng-Kai Zhang, Yi-Ge Zhang, Zhi Zhou et al.

A Manifold Perspective on the Statistical Generalization of Graph Neural Networks

Zhiyang Wang, Juan Cervino, Alejandro Ribeiro

ICML 2025arXiv:2502.09263

#91

Can Classic GNNs Be Strong Baselines for Graph-level Tasks? Simple Architectures Meet Excellence

Yuankai Luo, Lei Shi, Xiao-Ming Wu

ICLR 2025arXiv:2405.17163

#92

Port-Hamiltonian Architectural Bias for Long-Range Propagation in Deep Graph Networks

Simon Heilig, Alessio Gravina, Alessandro Trenta et al.

ICLR 2024arXiv:2402.04284

#93

PRES: Toward Scalable Memory-Based Dynamic Graph Neural Networks

Junwei Su, Difan Zou, Chuan Wu

AAAI 2025arXiv:2412.16447

#94

A Generalizable Anomaly Detection Method in Dynamic Graphs

Xiao Yang, Xuejiao Zhao, Zhiqi Shen

AAAI 2025arXiv:2412.15589

#95

Pre-Training Graph Neural Networks on Molecules by Using Subgraph-Conditioned Graph Information Bottleneck

Van Thuy Hoang, O-Joun Lee

CVPR 2024arXiv:2312.01280

#96

Brain Decodes Deep Nets

Huzheng Yang, James Gee, Jianbo Shi

ICML 2024arXiv:2312.01538

#97

Recurrent Distance Filtering for Graph Representation Learning

Yuhui Ding, Antonio Orvieto, Bobby He et al.

graph representation learningmessage passinggraph transformerspositional encoding+3

ICLR 2024arXiv:2311.01276

#98

Neural Atoms: Propagating Long-range Interaction in Molecular Graphs through Efficient Communication Channel

Xuan Li, Zhanke Zhou, Jiangchao Yao et al.

12

ICLR 2025arXiv:2502.03201

#99

SpaceGNN: Multi-Space Graph Neural Network for Node Anomaly Detection with Extremely Limited Labels

Xiangyu Dong, Xingyi Zhang, Lei Chen et al.

12

AAAI 2024arXiv:2401.04984

#100

MGNet: Learning Correspondences via Multiple Graphs

Dai Luanyuan, Xiaoyu Du, Hanwang Zhang et al.

correspondence learninggraph neural networksmultiple graph fusionlocal graph construction+3

12