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 / 284 papers shown

Title
Unifying over-smoothing and over-squashing in graph neural networks: A physics informed approach and beyond Zhiqi Shao Dai Shi Andi Han Yi Guo Qianchuan Zhao Junbin Gao 24 11 0 06 Sep 2023
Self-pruning Graph Neural Network for Predicting Inflammatory Disease Activity in Multiple Sclerosis from Brain MR Images Chinmay Prabhakar Hongwei Bran Li Johannes C. Paetzold T. Loehr Chen Niu Mark Muhlau Daniel Rueckert Benedikt Wiestler Bjoern H. Menze MedIm AI4CE 19 5 0 31 Aug 2023
Curvature-based Pooling within Graph Neural Networks Cedric Sanders Andreas Roth Thomas Liebig 33 5 0 31 Aug 2023
Enhancing Graph Transformers with Hierarchical Distance Structural Encoding Yuan Luo Hongkang Li Lei Shi Xiao-Ming Wu 23 7 0 22 Aug 2023
Investigating the Interplay between Features and Structures in Graph Learning Daniele Castellana Federico Errica 23 3 0 18 Aug 2023
Half-Hop: A graph upsampling approach for slowing down message passing Mehdi Azabou Venkataraman Ganesh S. Thakoor Chi-Heng Lin Lakshmi Sathidevi Ran Liu Michal Valko Petar Velickovic Eva L. Dyer 16 20 0 17 Aug 2023
The Expressive Power of Graph Neural Networks: A Survey Bingxue Zhang Changjun Fan Shixuan Liu Kuihua Huang Xiang Zhao Jin-Yu Huang Zhong Liu 40 19 0 16 Aug 2023
Weisfeiler and Lehman Go Paths: Learning Topological Features via Path Complexes Quang Truong Peter Chin GNN 19 7 0 13 Aug 2023
Target-aware Variational Auto-encoders for Ligand Generation with Multimodal Protein Representation Learning Haoxiang Luo Gang Sun 22 2 0 02 Aug 2023
CTAGE: Curvature-Based Topology-Aware Graph Embedding for Learning Molecular Representations Yili Chen Zhengyu Li Zheng Wan Hui Yu Xian Wei 21 0 0 25 Jul 2023
QDC: Quantum Diffusion Convolution Kernels on Graphs Thomas Markovich GNN 10 3 0 20 Jul 2023
How Curvature Enhance the Adaptation Power of Framelet GCNs Dai Shi Yi Guo Zhiqi Shao Junbin Gao 16 14 0 19 Jul 2023
Correlation-aware Spatial-Temporal Graph Learning for Multivariate Time-series Anomaly Detection Yu Zheng Huan Yee Koh Ming Jin Lianhua Chi Khoa T. Phan Shirui Pan Yi-Ping Phoebe Chen Wei Xiang AI4TS 10 24 0 17 Jul 2023
Graph Positional and Structural Encoder Semih Cantürk Renming Liu Olivier Lapointe-Gagné Vincent Létourneau Guy Wolf Dominique Beaini Ladislav Rampášek 31 13 0 14 Jul 2023
Frameless Graph Knowledge Distillation Dai Shi Zhiqi Shao Yi Guo Junbin Gao 26 4 0 13 Jul 2023
Improving Heterogeneous Graph Learning with Weighted Mixed-Curvature Product Manifold Tuc Nguyen-Van Dung D. Le The-Anh Ta 12 1 0 10 Jul 2023
Exploring & Exploiting High-Order Graph Structure for Sparse Knowledge Graph Completion Tao He Ming Liu Yixin Cao Zekun Wang Zihao Zheng Zheng Chu Bing Qin 8 2 0 29 Jun 2023
Diffusion-Jump GNNs: Homophiliation via Learnable Metric Filters Ahmed Begga Francisco Escolano M. Lozano Edwin R. Hancock 13 2 0 29 Jun 2023
Torsion Graph Neural Networks Cong Shen Xiang Liu Jiawei Luo Kelin Xia 22 0 0 23 Jun 2023
Curvature-enhanced Graph Convolutional Network for Biomolecular Interaction Prediction Cong Shen Pingjian Ding Junjie Wee Jialin Bi Jiawei Luo Kelin Xia GNN 6 6 0 23 Jun 2023
UUKG: Unified Urban Knowledge Graph Dataset for Urban Spatiotemporal Prediction Yansong NING Hao Liu Hao Wang Zhenyu Zeng Hui Xiong AI4TS 16 24 0 20 Jun 2023
P-tensors: a General Formalism for Constructing Higher Order Message Passing Networks Tianyi Sun Andrew R. Hands Risi Kondor 8 2 0 19 Jun 2023
How does over-squashing affect the power of GNNs? Francesco Di Giovanni T. Konstantin Rusch Michael M. Bronstein Andreea Deac Marc Lackenby Siddhartha Mishra Petar Velivcković 21 34 0 06 Jun 2023
Learning Probabilistic Symmetrization for Architecture Agnostic Equivariance Jinwoo Kim Tien Dat Nguyen Ayhan Suleymanzade Hyeokjun An Seunghoon Hong 40 23 0 05 Jun 2023
Towards Deep Attention in Graph Neural Networks: Problems and Remedies Soo Yong Lee Fanchen Bu Jaemin Yoo Kijung Shin GNN 11 30 0 04 Jun 2023
Is Rewiring Actually Helpful in Graph Neural Networks? Domenico Tortorella A. Micheli AI4CE 27 2 0 31 May 2023
Graph Inductive Biases in Transformers without Message Passing Liheng Ma Chen Lin Derek Lim Adriana Romero Soriano P. Dokania Mark J. Coates Philip H. S. Torr Ser-Nam Lim AI4CE 12 86 0 27 May 2023
From Latent Graph to Latent Topology Inference: Differentiable Cell Complex Module Claudio Battiloro Indro Spinelli Lev Telyatnikov Michael M. Bronstein Simone Scardapane P. Lorenzo BDL 21 14 0 25 May 2023
Union Subgraph Neural Networks Jiaxing Xu Aihu Zhang Qingtian Bian Vijay Prakash Dwivedi Yiping Ke GNN 19 6 0 25 May 2023
Mol-PECO: a deep learning model to predict human olfactory perception from molecular structures Mengji Zhang Yusuke Hiki Akira Funahashi Tetsuya J. Kobayashi 11 0 0 21 May 2023
Edge Directionality Improves Learning on Heterophilic Graphs Emanuele Rossi Bertrand Charpentier Francesco Di Giovanni Fabrizio Frasca Stephan Günnemann Michael M. Bronstein 15 56 0 17 May 2023
Addressing Heterophily in Node Classification with Graph Echo State Networks A. Micheli Domenico Tortorella 11 8 0 14 May 2023
DRew: Dynamically Rewired Message Passing with Delay Benjamin Gutteridge Xiaowen Dong Michael M. Bronstein Francesco Di Giovanni 27 58 0 13 May 2023
Structural Group Unfairness: Measurement and Mitigation by means of the Effective Resistance Adrián Arnaiz-Rodríguez Georgina Curto Nuria Oliver 16 0 0 05 May 2023
Beyond Homophily: Reconstructing Structure for Graph-agnostic Clustering Erlin Pan Zhao Kang 29 35 0 03 May 2023
Leveraging Label Non-Uniformity for Node Classification in Graph Neural Networks Feng Ji See Hian Lee Hanyang Meng Kai Zhao Jielong Yang Wee Peng Tay 36 12 0 29 Apr 2023
Dynamic Graph Representation Learning with Neural Networks: A Survey Leshanshui Yang Sébastien Adam Clément Chatelain AI4TS AI4CE 26 14 0 12 Apr 2023
Feudal Graph Reinforcement Learning Tommaso Marzi Arshjot Khehra Andrea Cini C. Alippi 22 0 0 11 Apr 2023
Hyperbolic Geometric Graph Representation Learning for Hierarchy-imbalance Node Classification Xingcheng Fu Yuecen Wei Qingyun Sun Haonan Yuan Jia Wu Hao Peng Jianxin Li AI4CE 22 24 0 11 Apr 2023
Projections of Model Spaces for Latent Graph Inference Haitz Sáez de Ocáriz Borde Alvaro Arroyo Ingmar Posner 19 9 0 21 Mar 2023
Tangent Bundle Convolutional Learning: from Manifolds to Cellular Sheaves and Back Claudio Battiloro Zhiyang Wang Hans Riess P. Di Lorenzo Alejandro Ribeiro 23 9 0 20 Mar 2023
A Survey on Oversmoothing in Graph Neural Networks T. Konstantin Rusch Michael M. Bronstein Siddhartha Mishra 16 184 0 20 Mar 2023
Molecular Property Prediction by Semantic-invariant Contrastive Learning Ziqiao Zhang Ailin Xie Jihong Guan Shuigeng Zhou 12 5 0 13 Mar 2023
Exphormer: Sparse Transformers for Graphs Hamed Shirzad A. Velingker B. Venkatachalam Danica J. Sutherland A. Sinop 11 96 0 10 Mar 2023
Node-Specific Space Selection via Localized Geometric Hyperbolicity in Graph Neural Networks See Hian Lee Feng Ji Wee Peng Tay 19 1 0 03 Mar 2023
Specformer: Spectral Graph Neural Networks Meet Transformers Deyu Bo Chuan Shi Lele Wang Renjie Liao 69 78 0 02 Mar 2023
Diffusing Graph Attention Daniel Glickman Eran Yahav GNN 28 3 0 01 Mar 2023
Drop Edges and Adapt: a Fairness Enforcing Fine-tuning for Graph Neural Networks Indro Spinelli Riccardo Bianchini Simone Scardapane 16 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 17 5 0 17 Feb 2023
Understanding Oversquashing in GNNs through the Lens of Effective Resistance Mitchell Black Zhengchao Wan A. Nayyeri Yusu Wang 25 63 0 14 Feb 2023