"graph neural networks" Papers
189 papers found • Page 4 of 4
On Which Nodes Does GCN Fail? Enhancing GCN From the Node Perspective
Jincheng Huang, Jialie SHEN, Xiaoshuang Shi et al.
Open Ad Hoc Teamwork with Cooperative Game Theory
Jianhong Wang, Yang Li, Yuan Zhang et al.
PAC-Bayesian Generalization Bounds for Knowledge Graph Representation Learning
Jaejun Lee, Minsung Hwang, Joyce Whang
PANDA: Expanded Width-Aware Message Passing Beyond Rewiring
Jeongwhan Choi, Sumin Parksumin, Hyowon Wi et al.
PGODE: Towards High-quality System Dynamics Modeling
Xiao Luo, Yiyang Gu, Huiyu Jiang et al.
PhAST: Physics-Aware, Scalable, and Task-Specific GNNs for Accelerated Catalyst Design
Alexandre Duval, Victor Schmidt, Santiago Miret et al.
Poincaré Differential Privacy for Hierarchy-Aware Graph Embedding
Yuecen Wei, Haonan Yuan, Xingcheng Fu et al.
Position: Future Directions in the Theory of Graph Machine Learning
Christopher Morris, Fabrizio Frasca, Nadav Dym et al.
Position: Graph Foundation Models Are Already Here
Haitao Mao, Zhikai Chen, Wenzhuo Tang et al.
Position: Relational Deep Learning - Graph Representation Learning on Relational Databases
Matthias Fey, Weihua Hu, Kexin Huang et al.
Predicting and Interpreting Energy Barriers of Metallic Glasses with Graph Neural Networks
Haoyu Li, Shichang Zhang, Longwen Tang et al.
Predicting Lagrangian Multipliers for Mixed Integer Linear Programs
Francesco Demelas, Joseph Roux, Mathieu Lacroix et al.
PreRoutGNN for Timing Prediction with Order Preserving Partition: Global Circuit Pre-training, Local Delay Learning and Attentional Cell Modeling
Ruizhe Zhong, Junjie Ye, Zhentao Tang et al.
Prometheus: Out-of-distribution Fluid Dynamics Modeling with Disentangled Graph ODE
Hao Wu, Huiyuan Wang, kun wang et al.
Provably Powerful Graph Neural Networks for Directed Multigraphs
Beni Egressy, Luc von Niederhäusern, Jovan Blanuša et al.
Quantum Positional Encodings for Graph Neural Networks
Slimane Thabet, Mehdi Djellabi, Igor Sokolov et al.
Question Calibration and Multi-Hop Modeling for Temporal Question Answering
Chao Xue, Di Liang, Pengfei Wang et al.
REST: Efficient and Accelerated EEG Seizure Analysis through Residual State Updates
Arshia Afzal, Grigorios Chrysos, Volkan Cevher et al.
Rethinking Independent Cross-Entropy Loss For Graph-Structured Data
Rui Miao, Kaixiong Zhou, Yili Wang et al.
Revisiting Graph-Based Fraud Detection in Sight of Heterophily and Spectrum
Fan Xu, Nan Wang, Hao Wu et al.
Sign is Not a Remedy: Multiset-to-Multiset Message Passing for Learning on Heterophilic Graphs
Langzhang Liang, Sunwoo Kim, Kijung Shin et al.
Structure Your Data: Towards Semantic Graph Counterfactuals
Angeliki Dimitriou, Maria Lymperaiou, Giorgos Filandrianos et al.
Subgraphormer: Unifying Subgraph GNNs and Graph Transformers via Graph Products
Guy Bar Shalom, Beatrice Bevilacqua, Haggai Maron
Subhomogeneous Deep Equilibrium Models
Pietro Sittoni, Francesco Tudisco
The Expressive Power of Path-Based Graph Neural Networks
Caterina Graziani, Tamara Drucks, Fabian Jogl et al.
The Merit of River Network Topology for Neural Flood Forecasting
Nikolas Kirschstein, Yixuan Sun
TopoGCL: Topological Graph Contrastive Learning
Yuzhou Chen, Jose Frias, Yulia Gel
Towards General Algorithm Discovery for Combinatorial Optimization: Learning Symbolic Branching Policy from Bipartite Graph
Yufei Kuang, Jie Wang, Yuyan Zhou et al.
Towards Inductive Robustness: Distilling and Fostering Wave-Induced Resonance in Transductive GCNs against Graph Adversarial Attacks
Ao Liu, Wenshan Li, Tao Li et al.
Translating Subgraphs to Nodes Makes Simple GNNs Strong and Efficient for Subgraph Representation Learning
Dongkwan Kim, Alice Oh
Two Heads Are Better Than One: Boosting Graph Sparse Training via Semantic and Topological Awareness
Guibin Zhang, Yanwei Yue, kun wang et al.
Uncertainty for Active Learning on Graphs
Dominik Fuchsgruber, Tom Wollschläger, Bertrand Charpentier et al.
Understanding Heterophily for Graph Neural Networks
Junfu Wang, Yuanfang Guo, Liang Yang et al.
Union Subgraph Neural Networks
Jiaxing Xu, Aihu Zhang, Qingtian Bian et al.
Unraveling the Impact of Heterophilic Structures on Graph Positive-Unlabeled Learning
Yuhao Wu, Jiangchao Yao, Bo Han et al.
Unsupervised Neighborhood Propagation Kernel Layers for Semi-supervised Node Classification
Sonny Achten, Francesco Tonin, Panagiotis Patrinos et al.
Verifying message-passing neural networks via topology-based bounds tightening
Christopher Hojny, Shiqiang Zhang, Juan Campos et al.
Weisfeiler and Lehman Go Paths: Learning Topological Features via Path Complexes
Quang Truong, Peter Chin
Weisfeiler Leman for Euclidean Equivariant Machine Learning
Snir Hordan, Tal Amir, Nadav Dym