Oversquashing in GNNs through the lens of information contraction and graph expansion

6 August 2022

Papers citing "Oversquashing in GNNs through the lens of information contraction and graph expansion"

22 / 22 papers shown

Title
Cayley Graph Propagation JJ Wilson Maya Bechler-Speicher Petar Veličković 173 6 0 04 Oct 2024
Joint Graph Rewiring and Feature Denoising via Spectral Resonance Jonas Linkerhagner Cheng Shi Ivan Dokmanić 160 0 0 13 Aug 2024
Conditional Shift-Robust Conformal Prediction for Graph Neural Network Akansha Agrawal UQCV 169 1 0 20 May 2024
Adaptive Message Passing: A General Framework to Mitigate Oversmoothing, Oversquashing, and Underreaching Federico Errica Henrik Christiansen Viktor Zaverkin Takashi Maruyama Mathias Niepert Francesco Alesiani 117 10 0 27 Dec 2023
Long Range Graph Benchmark Vijay Prakash Dwivedi Ladislav Rampášek Mikhail Galkin Alipanah Parviz Guy Wolf Anh Tuan Luu Dominique Beaini 76 209 0 16 Jun 2022
Understanding over-squashing and bottlenecks on graphs via curvature Jake Topping Francesco Di Giovanni B. Chamberlain Xiaowen Dong M. Bronstein 101 442 0 29 Nov 2021
DropGNN: Random Dropouts Increase the Expressiveness of Graph Neural Networks Pál András Papp Karolis Martinkus Lukas Faber Roger Wattenhofer GNN 55 140 0 11 Nov 2021
On the Bottleneck of Graph Neural Networks and its Practical Implications Uri Alon Eran Yahav GNN 79 685 0 09 Jun 2020
Generalization and Representational Limits of Graph Neural Networks Vikas Garg Stefanie Jegelka Tommi Jaakkola GNN 94 312 0 14 Feb 2020
Diffusion Improves Graph Learning Johannes Klicpera Stefan Weißenberger Stephan Günnemann GNN 121 704 0 28 Oct 2019
DropEdge: Towards Deep Graph Convolutional Networks on Node Classification Yu Rong Wenbing Huang Tingyang Xu Junzhou Huang 101 1,334 0 25 Jul 2019
A Comprehensive Survey on Graph Neural Networks Zonghan Wu Shirui Pan Fengwen Chen Guodong Long Chengqi Zhang Philip S. Yu FaML GNN AI4TS AI4CE 535 8,496 0 03 Jan 2019
How Powerful are Graph Neural Networks? Keyulu Xu Weihua Hu J. Leskovec Stefanie Jegelka GNN 210 7,623 0 01 Oct 2018
Representation Learning on Graphs with Jumping Knowledge Networks Keyulu Xu Chengtao Li Yonglong Tian Tomohiro Sonobe Ken-ichi Kawarabayashi Stefanie Jegelka GNN 490 1,977 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 584 3,112 0 04 Jun 2018
Graph Attention Networks Petar Velickovic Guillem Cucurull Arantxa Casanova Adriana Romero Pietro Lio Yoshua Bengio GNN 418 20,061 0 30 Oct 2017
Inductive Representation Learning on Large Graphs William L. Hamilton Z. Ying J. Leskovec 448 15,179 0 07 Jun 2017
Neural Message Passing for Quantum Chemistry Justin Gilmer S. Schoenholz Patrick F. Riley Oriol Vinyals George E. Dahl 435 7,431 0 04 Apr 2017
Semi-Supervised Classification with Graph Convolutional Networks Thomas Kipf Max Welling GNN SSL 573 28,964 0 09 Sep 2016
Discriminative Embeddings of Latent Variable Models for Structured Data H. Dai Bo Dai Le Song BDL 117 695 0 17 Mar 2016
Expanders via Local Edge Flips Zeyuan Allen-Zhu Aditya Bhaskara Silvio Lattanzi Vahab Mirrokni L. Orecchia 32 15 0 27 Oct 2015
Strong data-processing inequalities for channels and Bayesian networks Yury Polyanskiy Yihong Wu 38 113 0 25 Aug 2015