SIGN: Scalable Inception Graph Neural Networks

23 April 2020

Papers citing "SIGN: Scalable Inception Graph Neural Networks"

44 / 94 papers shown

Title
Discovering and Explaining the Representation Bottleneck of Graph Neural Networks from Multi-order Interactions Fang Wu Siyuan Li Lirong Wu Dragomir R. Radev Stan Z. Li 27 2 0 15 May 2022
NDGGNET-A Node Independent Gate based Graph Neural Networks Ye Tang Xuesong Yang Xinrui Liu Xiwei Zhao Zhangang Lin Changping Peng GNN 19 0 0 11 May 2022
GAP: Differentially Private Graph Neural Networks with Aggregation Perturbation Sina Sajadmanesh Ali Shahin Shamsabadi A. Bellet D. Gática-Pérez 30 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 Tengjiao Wang GNN 40 59 0 01 Mar 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 21 52 0 28 Feb 2022
Data Augmentation for Deep Graph Learning: A Survey Kaize Ding Zhe Xu Hanghang Tong Huan Liu OOD GNN 27 219 0 16 Feb 2022
Rewiring with Positional Encodings for Graph Neural Networks Rickard Brüel-Gabrielsson Mikhail Yurochkin Justin Solomon AI4CE 25 32 0 29 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 33 144 0 19 Jan 2022
Structure-Aware Label Smoothing for Graph Neural Networks Yiwei Wang Yujun Cai Keli Zhang Wei Wang Henghui Ding Muhao Chen Jing Tang Bryan Hooi 34 3 0 01 Dec 2021
Understanding over-squashing and bottlenecks on graphs via curvature Jake Topping Francesco Di Giovanni B. Chamberlain Xiaowen Dong M. Bronstein 64 426 0 29 Nov 2021
AutoHEnsGNN: Winning Solution to AutoGraph Challenge for KDD Cup 2020 Jin Xu Mingjian Chen Jianqiang Huang Xingyuan Tang Ke Hu Jian Li Jia Cheng Jun Lei 23 2 0 25 Nov 2021
VQ-GNN: A Universal Framework to Scale up Graph Neural Networks using Vector Quantization Mucong Ding Kezhi Kong Jingling Li Chen Zhu John P. Dickerson Furong Huang Tom Goldstein GNN MQ 33 47 0 27 Oct 2021
Graph-less Neural Networks: Teaching Old MLPs New Tricks via Distillation Shichang Zhang Yozen Liu Yizhou Sun Neil Shah 33 173 0 17 Oct 2021
Why Propagate Alone? Parallel Use of Labels and Features on Graphs Yangkun Wang Jiarui Jin Weinan Zhang Yongyi Yang Jiuhai Chen Quan Gan Yong Yu Zheng-Wei Zhang Zengfeng Huang David Wipf AAML 58 12 0 14 Oct 2021
IGLU: Efficient GCN Training via Lazy Updates S. Narayanan Aditya Sinha Prateek Jain Purushottam Kar Sundararajan Sellamanickam BDL 52 11 0 28 Sep 2021
Search For Deep Graph Neural Networks Guosheng Feng Chunnan Wang Hongzhi Wang GNN 32 23 0 21 Sep 2021
Efficient Variational Graph Autoencoders for Unsupervised Cross-domain Prerequisite Chains Irene Z Li Vanessa Yan Dragomir R. Radev GNN BDL 19 3 0 17 Sep 2021
Local Augmentation for Graph Neural Networks Songtao Liu Rex Ying Hanze Dong Lanqing Li Tingyang Xu Yu Rong P. Zhao Junzhou Huang Dinghao Wu 45 91 0 08 Sep 2021
Whole Brain Vessel Graphs: A Dataset and Benchmark for Graph Learning and Neuroscience (VesselGraph) Johannes C. Paetzold J. McGinnis Suprosanna Shit Ivan Ezhov Paul Büschl ... Anjany Sekuboyina Georgios Kaissis Ali Ertürk Stephan Günnemann Bjoern H. Menze 19 9 0 30 Aug 2021
Generative and Contrastive Self-Supervised Learning for Graph Anomaly Detection Yu Zheng Ming Jin Yixin Liu Lianhua Chi K. Phan Yi-Ping Phoebe Chen 22 122 0 23 Aug 2021
Evaluating Deep Graph Neural Networks Wentao Zhang Zeang Sheng Yuezihan Jiang Yikuan Xia Jun Gao Zhi-Xin Yang Tengjiao Wang GNN AI4CE 21 31 0 02 Aug 2021
Bridging the Gap between Spatial and Spectral Domains: A Unified Framework for Graph Neural Networks Zhiqian Chen Fanglan Chen Lei Zhang Taoran Ji Kaiqun Fu Liang Zhao Feng Chen Lingfei Wu Charu C. Aggarwal Chang-Tien Lu 44 18 0 21 Jul 2021
Large-scale graph representation learning with very deep GNNs and self-supervision Ravichandra Addanki Peter W. Battaglia David Budden Andreea Deac Jonathan Godwin ... Wai Lok Sibon Li Alvaro Sanchez-Gonzalez Jacklynn Stott S. Thakoor Petar Velivcković SSL AI4CE 27 25 0 20 Jul 2021
A Survey on Graph-Based Deep Learning for Computational Histopathology David Ahmedt-Aristizabal M. Armin Simon Denman Clinton Fookes L. Petersson GNN AI4CE 19 108 0 01 Jul 2021
Edge Proposal Sets for Link Prediction Abhay Singh Qian Huang Sijia Huang Omkar Bhalerao Horace He Ser-Nam Lim Austin R. Benson 11 16 0 30 Jun 2021
Training Graph Neural Networks with 1000 Layers Guohao Li Matthias Muller Guohao Li V. Koltun GNN AI4CE 51 235 0 14 Jun 2021
Residual Network and Embedding Usage: New Tricks of Node Classification with Graph Convolutional Networks Huixuan Chi Yuying Wang Qinfen Hao Hong Xia GNN 24 11 0 18 May 2021
Improving Graph Neural Networks with Simple Architecture Design S. Maurya Xin Liu T. Murata 26 47 0 17 May 2021
GMLP: Building Scalable and Flexible Graph Neural Networks with Feature-Message Passing Wentao Zhang Yu Shen Zheyu Lin Yang Li Xiaosen Li Wenbin Ouyang Yangyu Tao Zhi-Xin Yang Tengjiao Wang 27 9 0 20 Apr 2021
Do We Need Anisotropic Graph Neural Networks? Shyam A. Tailor Felix L. Opolka Pietro Lio Nicholas D. Lane 46 34 0 03 Apr 2021
Large Graph Convolutional Network Training with GPU-Oriented Data Communication Architecture S. Min Kun Wu Sitao Huang Mert Hidayetouglu Jinjun Xiong Eiman Ebrahimi Deming Chen Wen-mei W. Hwu GNN 10 67 0 04 Mar 2021
RA-GCN: Graph Convolutional Network for Disease Prediction Problems with Imbalanced Data Mahsa Ghorbani Anees Kazi M. Baghshah Hamid R. Rabiee Nassir Navab 27 72 0 27 Feb 2021
Dissecting the Diffusion Process in Linear Graph Convolutional Networks Yifei Wang Yisen Wang Jiansheng Yang Zhouchen Lin GNN 44 79 0 22 Feb 2021
Interpretable Stability Bounds for Spectral Graph Filters Henry Kenlay D. Thanou Xiaowen Dong 6 39 0 18 Feb 2021
Privacy-Preserving Graph Convolutional Networks for Text Classification Timour Igamberdiev Ivan Habernal GNN 31 33 0 10 Feb 2021
Utilising Graph Machine Learning within Drug Discovery and Development Thomas Gaudelet Ben Day Arian R. Jamasb Jyothish Soman Cristian Regep ... Jian Tang D. Roblin Tom L. Blundell M. Bronstein J. Taylor-King AI4CE 27 36 0 09 Dec 2020
Graph Neural Networks in Recommender Systems: A Survey Shiwen Wu Fei Sun Wentao Zhang Xu Xie Tengjiao Wang GNN 56 1,175 0 04 Nov 2020
Combining Label Propagation and Simple Models Out-performs Graph Neural Networks Qian Huang Horace He Abhay Singh Ser-Nam Lim Austin R. Benson 20 283 0 27 Oct 2020
Temporal Graph Networks for Deep Learning on Dynamic Graphs Emanuele Rossi B. Chamberlain Fabrizio Frasca D. Eynard Federico Monti M. Bronstein AI4CE 40 629 0 18 Jun 2020
Multi-scale Attributed Node Embedding Benedek Rozemberczki Carl Allen Rik Sarkar GNN 148 837 0 28 Sep 2019
Graph Neural Networks: A Review of Methods and Applications Jie Zhou Ganqu Cui Shengding Hu Zhengyan Zhang Cheng Yang Zhiyuan Liu Lifeng Wang Changcheng Li Maosong Sun AI4CE GNN 28 5,400 0 20 Dec 2018
Representation Learning on Graphs with Jumping Knowledge Networks Keyulu Xu Chengtao Li Yonglong Tian Tomohiro Sonobe Ken-ichi Kawarabayashi Stefanie Jegelka GNN 279 1,944 0 09 Jun 2018
Geometric deep learning on graphs and manifolds using mixture model CNNs Federico Monti Davide Boscaini Jonathan Masci Emanuele Rodolà Jan Svoboda M. Bronstein GNN 260 1,811 0 25 Nov 2016
Geometric deep learning: going beyond Euclidean data M. Bronstein Joan Bruna Yann LeCun Arthur Szlam P. Vandergheynst GNN 261 3,240 0 24 Nov 2016