Simplifying Graph Convolutional Networks

19 February 2019

Papers citing "Simplifying Graph Convolutional Networks"

50 / 1,391 papers shown

Title
GRAND+: Scalable Graph Random Neural Networks Wenzheng Feng Yuxiao Dong Tinglin Huang Ziqi Yin Xu Cheng Evgeny Kharlamov Jie Tang GNN 30 41 0 12 Mar 2022
Graph Summarization with Graph Neural Networks Maximilian Blasi M. Freudenreich Johannes Horvath David Richerby A. Scherp 38 0 0 11 Mar 2022
Anti-Oversmoothing in Deep Vision Transformers via the Fourier Domain Analysis: From Theory to Practice Peihao Wang Wenqing Zheng Tianlong Chen Zhangyang Wang ViT 33 127 0 09 Mar 2022
Pruning Graph Convolutional Networks to select meaningful graph frequencies for fMRI decoding Yassine El Ouahidi Hugo Tessier G. Lioi Nicolas Farrugia Bastien Pasdeloup Vincent Gripon GNN 41 2 0 09 Mar 2022
Defending Graph Convolutional Networks against Dynamic Graph Perturbations via Bayesian Self-supervision Jun Zhuang M. Hasan AAML 23 42 0 07 Mar 2022
Shift-Robust Node Classification via Graph Adversarial Clustering Qi Zhu Chao Zhang Chanyoung Park Carl Yang Jiawei Han OOD 25 6 0 07 Mar 2022
Object-centric Process Predictive Analytics Riccardo Galanti M. Leoni Nicoló Navarin Alan Marazzi 21 21 0 05 Mar 2022
Graph Representation Learning Beyond Node and Homophily You Li Bei Lin Binli Luo Ning Gui SSL 35 15 0 03 Mar 2022
Information Gain Propagation: a new way to Graph Active Learning with Soft Labels Wentao Zhang Yexin Wang Zhenbang You Meng Cao Ping Huang Jiulong Shan Zhi-Xin Yang Bin Cui AAML 38 19 0 02 Mar 2022
GAP: Differentially Private Graph Neural Networks with Aggregation Perturbation Sina Sajadmanesh Ali Shahin Shamsabadi A. Bellet D. Gática-Pérez 40 63 0 02 Mar 2022
PaSca: a Graph Neural Architecture Search System under the Scalable Paradigm Wentao Zhang Yu Shen Zheyu Lin Yang Li Xiaosen Li Wenbin Ouyang Yangyu Tao Zhi-Xin Yang Bin Cui GNN 42 60 0 01 Mar 2022
GraphWorld: Fake Graphs Bring Real Insights for GNNs John Palowitch Anton Tsitsulin Brandon Mayer Bryan Perozzi GNN 201 68 0 28 Feb 2022
Hyperbolic Graph Neural Networks: A Review of Methods and Applications Menglin Yang Min Zhou Zhihao Li Jiahong Liu Lujia Pan Hui Xiong Irwin King 29 52 0 28 Feb 2022
Sparse Graph Learning with Spectrum Prior for Deep Graph Convolutional Networks Jin Zeng Yang Liu Gene Cheung Wei Hu 23 4 0 28 Feb 2022
Differential equation and probability inspired graph neural networks for latent variable learning Zhuangwei Shi 19 3 0 28 Feb 2022
Addressing Over-Smoothing in Graph Neural Networks via Deep Supervision P. Elinas Edwin V. Bonilla AI4CE 34 5 0 25 Feb 2022
EIGNN: Efficient Infinite-Depth Graph Neural Networks Juncheng Liu Kenji Kawaguchi Bryan Hooi Yiwei Wang X. Xiao GNN 33 37 0 22 Feb 2022
Graph Auto-Encoder Via Neighborhood Wasserstein Reconstruction Mingyue Tang Carl Yang Pan Li GNN AI4CE 46 55 0 18 Feb 2022
Eliciting Structural and Semantic Global Knowledge in Unsupervised Graph Contrastive Learning Kaize Ding Yancheng Wang Yingzhen Yang Huan Liu 38 22 0 17 Feb 2022
Multivariate Time Series Forecasting with Dynamic Graph Neural ODEs Ming Jin Yu Zheng Yuanhao Li Siheng Chen B. Yang Shirui Pan BDL AI4TS AI4CE 43 101 0 17 Feb 2022
Data Augmentation for Deep Graph Learning: A Survey Kaize Ding Zhe Xu Yangqiu Song Huan Liu OOD GNN 34 220 0 16 Feb 2022
Out-Of-Distribution Generalization on Graphs: A Survey Haoyang Li Xin Eric Wang Ziwei Zhang Wenwu Zhu OOD CML 41 98 0 16 Feb 2022
Graph Neural Networks for Graphs with Heterophily: A Survey Xin-Yang Zheng Yi Wang Yixin Liu Ming Li Miao Zhang Di Jin Philip S. Yu Shirui Pan 33 216 0 14 Feb 2022
Random Laplacian Features for Learning with Hyperbolic Space Tao Yu Chris De Sa 22 8 0 14 Feb 2022
Neighborhood Contrastive Learning for Scientific Document Representations with Citation Embeddings Malte Ostendorff Nils Rethmeier Isabelle Augenstein Bela Gipp Georg Rehm 31 73 0 14 Feb 2022
Graph-adaptive Rectified Linear Unit for Graph Neural Networks Yifei Zhang Hao Zhu Ziqiao Meng Piotr Koniusz Irwin King 40 32 0 13 Feb 2022
Geometric Graph Representation Learning via Maximizing Rate Reduction Xiaotian Han Zhimeng Jiang Ninghao Liu Qingquan Song Jundong Li Xia Hu 33 21 0 13 Feb 2022
Robust Graph Representation Learning for Local Corruption Recovery Bingxin Zhou Yuanhong Jiang Yu Guang Wang Jingwei Liang Junbin Gao Shirui Pan Xiaoqun Zhang OOD 46 12 0 10 Feb 2022
Deconstructing the Inductive Biases of Hamiltonian Neural Networks Nate Gruver Marc Finzi Samuel Stanton A. Wilson AI4CE 31 40 0 10 Feb 2022
Neural Sheaf Diffusion: A Topological Perspective on Heterophily and Oversmoothing in GNNs Cristian Bodnar Francesco Di Giovanni B. Chamberlain Pietro Lio Michael M. Bronstein 37 171 0 09 Feb 2022
FMP: Toward Fair Graph Message Passing against Topology Bias Zhimeng Jiang Xiaotian Han Chao Fan Zirui Liu Na Zou Ali Mostafavi Xia Hu 24 48 0 08 Feb 2022
Simplified Graph Convolution with Heterophily Sudhanshu Chanpuriya Cameron Musco 27 25 0 08 Feb 2022
Neighbor2Seq: Deep Learning on Massive Graphs by Transforming Neighbors to Sequences Meng Liu Shuiwang Ji GNN 22 3 0 07 Feb 2022
MarkovGNN: Graph Neural Networks on Markov Diffusion Md. Khaledur Rahman Abhigya Agrawal A. Azad GNN BDL 29 2 0 05 Feb 2022
Convolutional Neural Networks on Graphs with Chebyshev Approximation, Revisited Mingguo He Zhewei Wei Ji-Rong Wen GNN 27 105 0 04 Feb 2022
Modularity-Aware Graph Autoencoders for Joint Community Detection and Link Prediction Guillaume Salha-Galvan J. Lutzeyer George Dasoulas Romain Hennequin Michalis Vazirgiannis 21 49 0 02 Feb 2022
SUGAR: Efficient Subgraph-level Training via Resource-aware Graph Partitioning Zihui Xue Yuedong Yang Mengtian Yang R. Marculescu 23 9 0 31 Jan 2022
MGNN: Graph Neural Networks Inspired by Distance Geometry Problem Guanyu Cui Zhewei Wei 32 8 0 31 Jan 2022
Over-smoothing Effect of Graph Convolutional Networks Fang Sun 36 1 0 30 Jan 2022
FedGCN: Convergence-Communication Tradeoffs in Federated Training of Graph Convolutional Networks Yuhang Yao Weizhao Jin Yu Yang Carlee Joe-Wong GNN FedML 60 19 0 28 Jan 2022
Confidence May Cheat: Self-Training on Graph Neural Networks under Distribution Shift Hongrui Liu Binbin Hu Xiao Wang Chuan Shi Qing Cui Jun Zhou 99 55 0 27 Jan 2022
Partition-Based Active Learning for Graph Neural Networks Jiaqi Ma Ziqiao Ma Joyce Chai Qiaozhu Mei 24 15 0 23 Jan 2022
How Expressive are Transformers in Spectral Domain for Graphs? Anson Bastos Abhishek Nadgeri Kuldeep Singh H. Kanezashi Toyotaro Suzumura I. Mulang' 27 12 0 23 Jan 2022
Toward Enhanced Robustness in Unsupervised Graph Representation Learning: A Graph Information Bottleneck Perspective Jihong Wang Minnan Luo Jundong Li Ziqi Liu Jun Zhou Qinghua Zheng AAML 23 5 0 21 Jan 2022
Fair Node Representation Learning via Adaptive Data Augmentation Öykü Deniz Köse Yanning Shen 22 31 0 21 Jan 2022
GenGNN: A Generic FPGA Framework for Graph Neural Network Acceleration Stefan Abi-Karam Yuqi He Rishov Sarkar Lakshmi Sathidevi Zihang Qiao Cong Hao GNN 14 14 0 20 Jan 2022
Informative Pseudo-Labeling for Graph Neural Networks with Few Labels Yayong Li Jie Yin Ling-Hao Chen 27 33 0 20 Jan 2022
Decoupling the Depth and Scope of Graph Neural Networks Hanqing Zeng Muhan Zhang Yinglong Xia Ajitesh Srivastava Andrey Malevich Rajgopal Kannan Viktor Prasanna Long Jin Ren Chen GNN 35 145 0 19 Jan 2022
Debiased Graph Neural Networks with Agnostic Label Selection Bias Shaohua Fan Xiao Wang Chuan Shi Kun Kuang Nian Liu Bai Wang AI4CE 46 38 0 19 Jan 2022
High-Level Synthesis Performance Prediction using GNNs: Benchmarking, Modeling, and Advancing Nan Wu Hang Yang Yuan Xie Pan Li Cong Hao 28 53 0 18 Jan 2022