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Simplifying Graph Convolutional Networks

19 February 2019

Papers citing "Simplifying Graph Convolutional Networks"

50 / 1,418 papers shown

Title
CAT-Walk: Inductive Hypergraph Learning via Set Walks Ali Behrouz Farnoosh Hashemi Sadaf Sadeghian Margo Seltzer 89 16 0 19 Jun 2023
Graph Self-Supervised Learning for Endoscopic Image Matching Manel Farhat A. Ben-Hamadou SSL 70 1 0 19 Jun 2023
SGFormer: Simplifying and Empowering Transformers for Large-Graph Representations Qitian Wu Wen-Long Zhao Chenxiao Yang Hengrui Zhang Fan Nie Haitian Jiang Yatao Bian Junchi Yan AI4CE 131 98 0 19 Jun 2023
Improving Generalizability of Graph Anomaly Detection Models via Data Augmentation Shuang Zhou Xiao Shi Huang Ninghao Liu Huachi Zhou F. Chung Longhai Huang 138 26 0 18 Jun 2023
Graph Ladling: Shockingly Simple Parallel GNN Training without Intermediate Communication A. Jaiswal Shiwei Liu Tianlong Chen Ying Ding Zhangyang Wang GNN 107 7 0 18 Jun 2023
HomoGCL: Rethinking Homophily in Graph Contrastive Learning Wenzhong Li Changdong Wang Hui Xiong Jian-Huang Lai 84 23 0 16 Jun 2023
GraphSHA: Synthesizing Harder Samples for Class-Imbalanced Node Classification Wenzhong Li Changdong Wang Hui Xiong Jian-Huang Lai 97 28 0 16 Jun 2023
The Split Matters: Flat Minima Methods for Improving the Performance of GNNs N. Lell A. Scherp 72 1 0 15 Jun 2023
Hyperbolic Representation Learning: Revisiting and Advancing Menglin Yang Min Zhou Rex Ying Yankai Chen Irwin King 87 23 0 15 Jun 2023
A Unified Framework of Graph Information Bottleneck for Robustness and Membership Privacy Enyan Dai Limeng Cui Zhengyang Wang Xianfeng Tang Yinghan Wang Mo Cheng Bin Yin Suhang Wang AAML 99 16 0 14 Jun 2023
Self-supervised Learning and Graph Classification under Heterophily Y. Ding Ziqiang Liu Hao Hao SSL 44 1 0 14 Jun 2023
NodeFormer: A Scalable Graph Structure Learning Transformer for Node Classification Qitian Wu Wentao Zhao Zenan Li David Wipf Junchi Yan 68 229 0 14 Jun 2023
A Simple and Scalable Graph Neural Network for Large Directed Graphs Seiji Maekawa Yuya Sasaki Makoto Onizuka GNN 65 0 0 14 Jun 2023
Finding the Missing-half: Graph Complementary Learning for Homophily-prone and Heterophily-prone Graphs Y. Zheng He Zhang V. Lee Yu Zheng Tianlin Li Shirui Pan 77 33 0 13 Jun 2023
NeuroGraph: Benchmarks for Graph Machine Learning in Brain Connectomics Anwar Said Roza G. Bayrak Hanyu Wang Mudassir Shabbir Daniel Moyer Catie Chang X. Koutsoukos 80 27 0 09 Jun 2023
On Performance Discrepancies Across Local Homophily Levels in Graph Neural Networks Donald Loveland Jiong Zhu Mark Heimann Benjamin Fish Michael T. Shaub Danai Koutra 116 7 0 08 Jun 2023
DualHGNN: A Dual Hypergraph Neural Network for Semi-Supervised Node Classification based on Multi-View Learning and Density Awareness Jianpeng Liao Jun Yan Qian Tao 47 2 0 07 Jun 2023
BeMap: Balanced Message Passing for Fair Graph Neural Network Xiao Lin Jian Kang Weilin Cong Hanghang Tong MoE 104 8 0 07 Jun 2023
Personalized Federated Domain Adaptation for Item-to-Item Recommendation Ziwei Fan Hao Ding Anoop Deoras T. Hoang 93 6 0 05 Jun 2023
Structure-free Graph Condensation: From Large-scale Graphs to Condensed Graph-free Data Xin Zheng Miao Zhang C. Chen Quoc Viet Hung Nguyen Xingquan Zhu Shirui Pan DD 120 69 0 05 Jun 2023
Towards Deep Attention in Graph Neural Networks: Problems and Remedies Soo Yong Lee Fanchen Bu Jaemin Yoo Kijung Shin GNN 61 31 0 04 Jun 2023
A Survey on Explainability of Graph Neural Networks Jaykumar Kakkad Jaspal Jannu Kartik Sharma Charu C. Aggarwal Sourav Medya 62 28 0 02 Jun 2023
Demystifying Structural Disparity in Graph Neural Networks: Can One Size Fit All? Haitao Mao Zhikai Chen Wei Jin Haoyu Han Yao Ma Tong Zhao Neil Shah Jiliang Tang 116 36 0 02 Jun 2023
SPGNN-API: A Transferable Graph Neural Network for Attack Paths Identification and Autonomous Mitigation Houssem Jmal Firas Hmida Nardine Basta Muhammad Ikram M. Kâafar Andy Walker AAML 57 2 0 31 May 2023
Node Embedding from Neural Hamiltonian Orbits in Graph Neural Networks Qiyu Kang Kai Zhao Yang Song Sijie Wang Wee Peng Tay 70 12 0 30 May 2023
Learning Strong Graph Neural Networks with Weak Information Yixin Liu Kaize Ding Jianling Wang V. Lee Huan Liu Shirui Pan 81 46 0 29 May 2023
Dink-Net: Neural Clustering on Large Graphs Yue Liu K. Liang Jun Xia Sihang Zhou Xihong Yang Xinwang Liu Stan Z. Li GNN 156 55 0 28 May 2023
Self-attention Dual Embedding for Graphs with Heterophily Yurui Lai Taiyan Zhang Rui Fan GNN 91 0 0 28 May 2023
Revisiting Generalized p-Laplacian Regularized Framelet GCNs: Convergence, Energy Dynamic and Training with Non-Linear Diffusion Dai Shi Zhiqi Shao Yi Guo Qianchuan Zhao Junbin Gao 100 1 0 25 May 2023
What functions can Graph Neural Networks compute on random graphs? The role of Positional Encoding Nicolas Keriven Samuel Vaiter 77 12 0 24 May 2023
Uncertainty Quantification over Graph with Conformalized Graph Neural Networks Kexin Huang Ying Jin Emmanuel Candès J. Leskovec 262 63 0 23 May 2023
Do Not Train It: A Linear Neural Architecture Search of Graph Neural Networks Peng Xu Lin Zhang Xuanzhou Liu Jiaqi Sun Yue Zhao Haiqing Yang Bei Yu GNN 78 9 0 23 May 2023
The Evolution of Distributed Systems for Graph Neural Networks and their Origin in Graph Processing and Deep Learning: A Survey Jana Vatter R. Mayer Hans-Arno Jacobsen GNN AI4TS AI4CE 96 29 0 23 May 2023
Continual Learning on Dynamic Graphs via Parameter Isolation Peiyan Zhang Yuchen Yan Chaozhuo Li Senzhang Wang Xing Xie Guojie Song Sunghun Kim 111 40 0 23 May 2023
Link Prediction without Graph Neural Networks Zexi Huang Mert Kosan A. Silva Ambuj K. Singh 112 3 0 23 May 2023
Causal-Based Supervision of Attention in Graph Neural Network: A Better and Simpler Choice towards Powerful Attention Hongjun Wang Jiyuan Chen Lun Du Qiang Fu Shi Han Xuan Song CML GNN 81 5 0 22 May 2023
A Fractional Graph Laplacian Approach to Oversmoothing Sohir Maskey Raffaele Paolino Aras Bacho Gitta Kutyniok 118 37 0 22 May 2023
Road Planning for Slums via Deep Reinforcement Learning Y. Zheng Hongyuan Su Jingtao Ding Depeng Jin Yong Li 80 14 0 22 May 2023
MMGP: a Mesh Morphing Gaussian Process-based machine learning method for regression of physical problems under non-parameterized geometrical variability F. Casenave B. Staber Xavier Roynard AI4CE 70 17 0 22 May 2023
Tokenized Graph Transformer with Neighborhood Augmentation for Node Classification in Large Graphs Jinsong Chen Chang-Shu Liu Kai-Xin Gao Gaichao Li Kun He 94 4 0 22 May 2023
Towards Complex Dynamic Physics System Simulation with Graph Neural ODEs Guangsi Shi Daokun Zhang Ming Jin Shirui Pan Philip S. Yu AI4CE 97 4 0 21 May 2023
Learning Continually on a Sequence of Graphs -- The Dynamical System Way Krishnan Raghavan Prasanna Balaprakash 80 0 0 19 May 2023
Ultra-High Resolution Segmentation with Ultra-Rich Context: A Novel Benchmark Deyi Ji Feng Zhao Hongtao Lu Mingyuan Tao Jieping Ye AI4TS 78 27 0 18 May 2023
Seq-HGNN: Learning Sequential Node Representation on Heterogeneous Graph Chenguang Du Kaichun Yao Hengshu Zhu Deqing Wang Fuzhen Zhuang Hui Xiong 65 6 0 18 May 2023
Extracting Low-/High- Frequency Knowledge from Graph Neural Networks and Injecting it into MLPs: An Effective GNN-to-MLP Distillation Framework Lirong Wu Haitao Lin Yufei Huang Tianyu Fan Stan Z. Li 96 29 0 18 May 2023
Simplifying Distributed Neural Network Training on Massive Graphs: Randomized Partitions Improve Model Aggregation Jiong Zhu Aishwarya N. Reganti E-Wen Huang Charles Dickens Nikhil S. Rao Karthik Subbian Danai Koutra GNN FedML 80 3 0 17 May 2023
FedHGN: A Federated Framework for Heterogeneous Graph Neural Networks Xinyu Fu Irwin King FedML 81 4 0 16 May 2023
Decoupled Graph Neural Networks for Large Dynamic Graphs Yanping Zheng Zhewei Wei Jiajun Liu GNN BDL AI4TS AI4CE 55 14 0 14 May 2023
Addressing Heterophily in Node Classification with Graph Echo State Networks Alessio Micheli Domenico Tortorella 100 8 0 14 May 2023
Towards Understanding the Generalization of Graph Neural Networks Huayi Tang Y. Liu GNN AI4CE 95 32 0 14 May 2023