Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs

18 December 2022

Papers citing "Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs"

50 / 55 papers shown

Title
Rethinking and Accelerating Graph Condensation: A Training-Free Approach with Class Partition Xin Gao Tong Chen Wentao Zhang Junliang Yu Guanhua Ye Quoc Viet Hung Nguyen 114 7 0 22 May 2024
The Expressive Power of Graph Neural Networks: A Survey Bingxue Zhang Changjun Fan Shixuan Liu Kuihua Huang Xiang Zhao Jin-Yu Huang Zhong Liu 188 23 0 16 Aug 2023
NodeFormer: A Scalable Graph Structure Learning Transformer for Node Classification Qitian Wu Wentao Zhao Zenan Li David Wipf Junchi Yan 52 222 0 14 Jun 2023
OrthoReg: Improving Graph-regularized MLPs via Orthogonality Regularization Hengrui Zhang Shen Wang V. Ioannidis Soji Adeshina Jiani Zhang Xiao Qin Christos Faloutsos Da Zheng George Karypis Philip S. Yu 57 4 0 31 Jan 2023
DIFFormer: Scalable (Graph) Transformers Induced by Energy Constrained Diffusion Qitian Wu Chenxiao Yang Wen-Long Zhao Yixuan He David Wipf Junchi Yan DiffM 62 87 0 23 Jan 2023
Geometric Knowledge Distillation: Topology Compression for Graph Neural Networks Chenxiao Yang Qitian Wu Junchi Yan 40 28 0 24 Oct 2022
MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP Initialization Xiaotian Han Tong Zhao Yozen Liu Xia Hu Neil Shah GNN 107 38 0 30 Sep 2022
Effects of Graph Convolutions in Multi-layer Networks Aseem Baranwal Kimon Fountoulakis Aukosh Jagannath 51 26 0 20 Apr 2022
On Provable Benefits of Depth in Training Graph Convolutional Networks Weilin Cong M. Ramezani M. Mahdavi 56 75 0 28 Oct 2021
Graph-less Neural Networks: Teaching Old MLPs New Tricks via Distillation Shichang Zhang Yozen Liu Yizhou Sun Neil Shah 81 185 0 17 Oct 2021
Subgroup Generalization and Fairness of Graph Neural Networks Jiaqi Ma Junwei Deng Qiaozhu Mei 70 82 0 29 Jun 2021
Graph-MLP: Node Classification without Message Passing in Graph Yang Hu Haoxuan You Zhecan Wang Zhicheng Wang Erjin Zhou Yue Gao 101 114 0 08 Jun 2021
Optimization of Graph Neural Networks: Implicit Acceleration by Skip Connections and More Depth Keyulu Xu Mozhi Zhang Stefanie Jegelka Kenji Kawaguchi GNN 42 78 0 10 May 2021
Graph Convolution for Semi-Supervised Classification: Improved Linear Separability and Out-of-Distribution Generalization Aseem Baranwal Kimon Fountoulakis Aukosh Jagannath OODD 100 76 0 13 Feb 2021
Graph Coarsening with Neural Networks Chen Cai Dingkang Wang Yusu Wang DD 176 67 0 02 Feb 2021
Scalable Graph Neural Networks via Bidirectional Propagation Ming Chen Zhewei Wei Bolin Ding Yaliang Li Ye Yuan Xiaoyong Du Ji-Rong Wen GNN 47 145 0 29 Oct 2020
On Graph Neural Networks versus Graph-Augmented MLPs Lei Chen Zhengdao Chen Joan Bruna 56 46 0 28 Oct 2020
Combining Label Propagation and Simple Models Out-performs Graph Neural Networks Qian Huang Horace He Abhay Singh Ser-Nam Lim Austin R. Benson 77 283 0 27 Oct 2020
On the linearity of large non-linear models: when and why the tangent kernel is constant Chaoyue Liu Libin Zhu M. Belkin 104 141 0 02 Oct 2020
How Neural Networks Extrapolate: From Feedforward to Graph Neural Networks Keyulu Xu Mozhi Zhang Jingling Li S. Du Ken-ichi Kawarabayashi Stefanie Jegelka MLT 101 312 0 24 Sep 2020
Towards Deeper Graph Neural Networks Meng Liu Hongyang Gao Shuiwang Ji GNN AI4CE 98 605 0 18 Jul 2020
Simple and Deep Graph Convolutional Networks Ming Chen Zhewei Wei Zengfeng Huang Bolin Ding Yaliang Li GNN 116 1,485 0 04 Jul 2020
Adaptive Universal Generalized PageRank Graph Neural Network Eli Chien Jianhao Peng Pan Li O. Milenkovic 261 738 0 14 Jun 2020
Evaluation of Neural Architectures Trained with Square Loss vs Cross-Entropy in Classification Tasks Like Hui M. Belkin UQCV AAML VLM 48 171 0 12 Jun 2020
Open Graph Benchmark: Datasets for Machine Learning on Graphs Weihua Hu Matthias Fey Marinka Zitnik Yuxiao Dong Hongyu Ren Bowen Liu Michele Catasta J. Leskovec 303 2,728 0 02 May 2020
SIGN: Scalable Inception Graph Neural Networks Fabrizio Frasca Emanuele Rossi D. Eynard B. Chamberlain M. Bronstein Federico Monti GNN 117 396 0 23 Apr 2020
Adaptive Propagation Graph Convolutional Network Indro Spinelli Simone Scardapane A. Uncini GNN 60 75 0 24 Feb 2020
Geom-GCN: Geometric Graph Convolutional Networks Hongbin Pei Bingzhen Wei Kevin Chen-Chuan Chang Yu Lei Bo Yang GNN 318 1,118 0 13 Feb 2020
Implicit Bias of Gradient Descent for Wide Two-layer Neural Networks Trained with the Logistic Loss Lénaïc Chizat Francis R. Bach MLT 114 338 0 11 Feb 2020
DropEdge: Towards Deep Graph Convolutional Networks on Node Classification Yu Rong Wenbing Huang Tingyang Xu Junzhou Huang 107 1,339 0 25 Jul 2019
GraphSAINT: Graph Sampling Based Inductive Learning Method Hanqing Zeng Hongkuan Zhou Ajitesh Srivastava Rajgopal Kannan Viktor Prasanna GNN 137 966 0 10 Jul 2019
Generalization Bounds of Stochastic Gradient Descent for Wide and Deep Neural Networks Yuan Cao Quanquan Gu MLT AI4CE 80 389 0 30 May 2019
Graph Neural Tangent Kernel: Fusing Graph Neural Networks with Graph Kernels S. Du Kangcheng Hou Barnabás Póczós Ruslan Salakhutdinov Ruosong Wang Keyulu Xu 130 276 0 30 May 2019
On the Inductive Bias of Neural Tangent Kernels A. Bietti Julien Mairal 81 257 0 29 May 2019
Provably Powerful Graph Networks Haggai Maron Heli Ben-Hamu Hadar Serviansky Y. Lipman 118 579 0 27 May 2019
Are Powerful Graph Neural Nets Necessary? A Dissection on Graph Classification Ting-Li Chen Song Bian Yizhou Sun 95 88 0 11 May 2019
Stability and Generalization of Graph Convolutional Neural Networks Saurabh Verma Zhi-Li Zhang GNN MLT 94 159 0 03 May 2019
On Exact Computation with an Infinitely Wide Neural Net Sanjeev Arora S. Du Wei Hu Zhiyuan Li Ruslan Salakhutdinov Ruosong Wang 215 923 0 26 Apr 2019
Simplifying Graph Convolutional Networks Felix Wu Tianyi Zhang Amauri Souza Christopher Fifty Tao Yu Kilian Q. Weinberger GNN 230 3,172 0 19 Feb 2019
Wide Neural Networks of Any Depth Evolve as Linear Models Under Gradient Descent Jaehoon Lee Lechao Xiao S. Schoenholz Yasaman Bahri Roman Novak Jascha Narain Sohl-Dickstein Jeffrey Pennington 211 1,101 0 18 Feb 2019
Fine-Grained Analysis of Optimization and Generalization for Overparameterized Two-Layer Neural Networks Sanjeev Arora S. Du Wei Hu Zhiyuan Li Ruosong Wang MLT 195 972 0 24 Jan 2019
Pitfalls of Graph Neural Network Evaluation Oleksandr Shchur Maximilian Mumme Aleksandar Bojchevski Stephan Günnemann GNN 162 1,359 0 14 Nov 2018
Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers Zeyuan Allen-Zhu Yuanzhi Li Yingyu Liang MLT 183 769 0 12 Nov 2018
Predict then Propagate: Graph Neural Networks meet Personalized PageRank Johannes Klicpera Aleksandar Bojchevski Stephan Günnemann GNN 216 1,686 0 14 Oct 2018
How Powerful are Graph Neural Networks? Keyulu Xu Weihua Hu J. Leskovec Stefanie Jegelka GNN 238 7,642 0 01 Oct 2018
Neural Tangent Kernel: Convergence and Generalization in Neural Networks Arthur Jacot Franck Gabriel Clément Hongler 267 3,195 0 20 Jun 2018
Representation Learning on Graphs with Jumping Knowledge Networks Keyulu Xu Chengtao Li Yonglong Tian Tomohiro Sonobe Ken-ichi Kawarabayashi Stefanie Jegelka GNN 493 1,981 0 09 Jun 2018
Relational inductive biases, deep learning, and graph networks Peter W. Battaglia Jessica B. Hamrick V. Bapst Alvaro Sanchez-Gonzalez V. Zambaldi ... Pushmeet Kohli M. Botvinick Oriol Vinyals Yujia Li Razvan Pascanu AI4CE NAI 747 3,119 0 04 Jun 2018
FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling Jie Chen Tengfei Ma Cao Xiao GNN 144 1,513 0 30 Jan 2018
Inductive Representation Learning on Large Graphs William L. Hamilton Z. Ying J. Leskovec 498 15,232 0 07 Jun 2017