Understanding over-squashing and bottlenecks on graphs via curvature

29 November 2021

Jake Topping

Francesco Di Giovanni

Papers citing "Understanding over-squashing and bottlenecks on graphs via curvature"

50 / 287 papers shown

Title
Drop Edges and Adapt: a Fairness Enforcing Fine-tuning for Graph Neural Networks Indro Spinelli Riccardo Bianchini Simone Scardapane 26 1 0 22 Feb 2023
Building Shortcuts between Distant Nodes with Biaffine Mapping for Graph Convolutional Networks Acong Zhang Jincheng Huang Ping Li Kaizheng Zhang GNN 27 5 0 17 Feb 2023
Understanding Oversquashing in GNNs through the Lens of Effective Resistance Mitchell Black Zhengchao Wan A. Nayyeri Yusu Wang 32 64 0 14 Feb 2023
Homophily-oriented Heterogeneous Graph Rewiring Jiayan Guo Lun Du Wendong Bi Qiang Fu Xiaojun Ma Xu Chen Shi Han Dongmei Zhang Yan Zhang 27 26 0 13 Feb 2023
Graph Neural Network-Inspired Kernels for Gaussian Processes in Semi-Supervised Learning Zehao Niu M. Anitescu Jing Chen BDL 19 4 0 12 Feb 2023
Attending to Graph Transformers Luis Muller Mikhail Galkin Christopher Morris Ladislav Rampášek 52 86 0 08 Feb 2023
On Over-Squashing in Message Passing Neural Networks: The Impact of Width, Depth, and Topology Francesco Di Giovanni Lorenzo Giusti Federico Barbero Giulia Luise Pietro Lio Michael M. Bronstein 48 112 0 06 Feb 2023
Reply to: Inability of a graph neural network heuristic to outperform greedy algorithms in solving combinatorial optimization problems M. Schuetz J. K. Brubaker H. Katzgraber 33 2 0 03 Feb 2023
Reply to: Modern graph neural networks do worse than classical greedy algorithms in solving combinatorial optimization problems like maximum independent set M. Schuetz J. K. Brubaker H. Katzgraber 31 10 0 03 Feb 2023
Ordered GNN: Ordering Message Passing to Deal with Heterophily and Over-smoothing Yunchong Song Cheng Zhou Xinbing Wang Zhouhan Lin 32 63 0 03 Feb 2023
Graph Neural Networks for temporal graphs: State of the art, open challenges, and opportunities Antonio Longa Veronica Lachi G. Santin Monica Bianchini Bruno Lepri Pietro Lió F. Scarselli Andrea Passerini AI4CE 25 50 0 02 Feb 2023
Curvature Filtrations for Graph Generative Model Evaluation Joshua Southern Jeremy Wayland Michael M. Bronstein Bastian Alexander Rieck 23 14 0 30 Jan 2023
On the Connection Between MPNN and Graph Transformer Chen Cai Truong-Son Hy Rose Yu Yusu Wang 39 51 0 27 Jan 2023
Graph Scattering beyond Wavelet Shackles Christian Koke Gitta Kutyniok 24 4 0 26 Jan 2023
Limitless stability for Graph Convolutional Networks Christian Koke 52 3 0 26 Jan 2023
On the Expressive Power of Geometric Graph Neural Networks Chaitanya K. Joshi Cristian Bodnar Simon V. Mathis Taco Cohen Pietro Liò 55 83 0 23 Jan 2023
Self-organization Preserved Graph Structure Learning with Principle of Relevant Information Qingyun Sun Jianxin Li Beining Yang Xingcheng Fu Hao Peng Philip S. Yu 19 11 0 30 Dec 2022
A Generalization of ViT/MLP-Mixer to Graphs Xiaoxin He Bryan Hooi T. Laurent Adam Perold Yann LeCun Xavier Bresson 47 88 0 27 Dec 2022
Leave Graphs Alone: Addressing Over-Squashing without Rewiring Adam Santoro Ashish Vaswani 22 11 0 13 Dec 2022
On the Trade-off between Over-smoothing and Over-squashing in Deep Graph Neural Networks Jhony H. Giraldo Konstantinos Skianis T. Bouwmans Fragkiskos D. Malliaros 24 45 0 05 Dec 2022
kHGCN: Tree-likeness Modeling via Continuous and Discrete Curvature Learning Menglin Yang Min Zhou Lujia Pan Irwin King 29 18 0 04 Dec 2022
Semi-Supervised Heterogeneous Graph Learning with Multi-level Data Augmentation Yingxi Chen Siwei Qiang Mingming Ha Xiaolei Liu Shaoshuai Li Lingfeng Yuan Xiaobo Guo Zheng Hua Zhu 19 2 0 30 Nov 2022
On the Ability of Graph Neural Networks to Model Interactions Between Vertices Noam Razin Tom Verbin Nadav Cohen 23 10 0 29 Nov 2022
FakeEdge: Alleviate Dataset Shift in Link Prediction Kaiwen Dong Yijun Tian Zhichun Guo Yang Yang Nitesh V. Chawla 21 12 0 29 Nov 2022
Revisiting Over-smoothing and Over-squashing Using Ollivier-Ricci Curvature K. Nguyen Hieu Nong T. Nguyen Nhat Ho Khuong N. Nguyen Vinh Phu Nguyen 27 63 0 28 Nov 2022
Latent Graph Inference using Product Manifolds Haitz Sáez de Ocáriz Borde Anees Kazi Federico Barbero Pietro Lio BDL 40 19 0 26 Nov 2022
From Node Interaction to Hop Interaction: New Effective and Scalable Graph Learning Paradigm Jie Chen Zilong Li Ying Zhu Junping Zhang Jian Pu 36 8 0 21 Nov 2022
EGRC-Net: Embedding-induced Graph Refinement Clustering Network Zhihao Peng Hui Liu Yuheng Jia Junhui Hou 27 6 0 19 Nov 2022
Changes from Classical Statistics to Modern Statistics and Data Science Kai Zhang Shan-Yu Liu M. Xiong 31 0 0 30 Oct 2022
Beyond Homophily with Graph Echo State Networks Domenico Tortorella A. Micheli 24 4 0 27 Oct 2022
Meta-node: A Concise Approach to Effectively Learn Complex Relationships in Heterogeneous Graphs Jiwoong Park Jisu Jeong Kyungmin Kim Jin Young Choi 24 1 0 26 Oct 2022
Thermodynamics-informed neural networks for physically realistic mixed reality Quercus Hernandez Alberto Badías Francisco Chinesta Elías Cueto PINN AI4CE 22 16 0 24 Oct 2022
Transformers over Directed Acyclic Graphs Yu Luo Veronika Thost Lei Shi GNN AI4CE 40 16 0 24 Oct 2022
Geometric Knowledge Distillation: Topology Compression for Graph Neural Networks Chenxiao Yang Qitian Wu Junchi Yan 21 26 0 24 Oct 2022
Ollivier-Ricci Curvature for Hypergraphs: A Unified Framework Corinna Coupette Sebastian Dalleiger Bastian Alexander Rieck 19 13 0 21 Oct 2022
FoSR: First-order spectral rewiring for addressing oversquashing in GNNs Kedar Karhadkar P. Banerjee Guido Montúfar 31 56 0 21 Oct 2022
Extending Graph Transformers with Quantum Computed Aggregation Slimane Thabet Romain Fouilland L. Henriet GNN 33 3 0 19 Oct 2022
Anti-Symmetric DGN: a stable architecture for Deep Graph Networks Alessio Gravina D. Bacciu Claudio Gallicchio GNN 21 50 0 18 Oct 2022
A Practical, Progressively-Expressive GNN Lingxiao Zhao Louis Härtel Neil Shah L. Akoglu 32 17 0 18 Oct 2022
Generalized energy and gradient flow via graph framelets Andi Han Dai Shi Zhiqi Shao Junbin Gao 75 13 0 08 Oct 2022
Expander Graph Propagation Andreea Deac Marc Lackenby Petar Velivcković 96 52 0 06 Oct 2022
Gradient Gating for Deep Multi-Rate Learning on Graphs T. Konstantin Rusch B. Chamberlain Michael W. Mahoney Michael M. Bronstein Siddhartha Mishra 79 53 0 02 Oct 2022
Graph Neural Networks for Link Prediction with Subgraph Sketching B. Chamberlain S. Shirobokov Emanuele Rossi Fabrizio Frasca Thomas Markovich Nils Y. Hammerla Michael M. Bronstein Max Hansmire 51 77 0 30 Sep 2022
From Local to Global: Spectral-Inspired Graph Neural Networks Ningyuan Huang Soledad Villar Carey E. Priebe Da Zheng Cheng-Fu Huang Lin F. Yang Vladimir Braverman 23 14 0 24 Sep 2022
Memory-Augmented Graph Neural Networks: A Brain-Inspired Review Guixiang Ma Vy A. Vo Ted Willke Nesreen Ahmed 35 1 0 22 Sep 2022
Make Heterophily Graphs Better Fit GNN: A Graph Rewiring Approach Wendong Bi Lun Du Qiang Fu Yanlin Wang Shi Han Dongmei Zhang 27 27 0 17 Sep 2022
On the Robustness of Graph Neural Diffusion to Topology Perturbations Yang Song Qiyu Kang Sijie Wang Zhao Kai Wee Peng Tay DiffM AAML 57 35 0 16 Sep 2022
Toward Robust Graph Semi-Supervised Learning against Extreme Data Scarcity Kaize Ding E. Nouri Guoqing Zheng Huan Liu Ryen W. White 26 9 0 26 Aug 2022
Position-aware Structure Learning for Graph Topology-imbalance by Relieving Under-reaching and Over-squashing Qingyun Sun Jianxin Li Haonan Yuan Xingcheng Fu Hao Peng Cheng Ji Qian Li Philip S. Yu 16 37 0 17 Aug 2022
Oversquashing in GNNs through the lens of information contraction and graph expansion P. Banerjee Kedar Karhadkar Yu Guang Wang Uri Alon Guido Montúfar 21 44 0 06 Aug 2022