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
Continual Learning on Graphs: Challenges, Solutions, and Opportunities Xikun Zhang Dongjin Song Dacheng Tao CLL 26 7 0 18 Feb 2024
Scalable Graph Self-Supervised Learning Ali Saheb Pasand Reza Moravej Mahdi Biparva Raika Karimi Ali Ghodsi SSL 11 0 0 14 Feb 2024
Position: Topological Deep Learning is the New Frontier for Relational Learning Theodore Papamarkou Tolga Birdal Michael M. Bronstein Gunnar Carlsson Justin Curry ... Petar Velickovic Bei Wang Yusu Wang Guo-Wei Wei Ghada Zamzmi AI4CE 54 24 0 14 Feb 2024
CoRe-GD: A Hierarchical Framework for Scalable Graph Visualization with GNNs Florian Grötschla Joël Mathys Robert Veres Roger Wattenhofer 16 3 0 09 Feb 2024
Similarity-based Neighbor Selection for Graph LLMs Rui Li Jiwei Li Jiawei Han Guoyin Wang 20 3 0 06 Feb 2024
Future Directions in the Theory of Graph Machine Learning Christopher Morris Fabrizio Frasca Nadav Dym Haggai Maron .Ismail .Ilkan Ceylan Ron Levie Derek Lim Michael M. Bronstein Martin Grohe Stefanie Jegelka AI4CE 30 4 0 03 Feb 2024
Position: Graph Foundation Models are Already Here Haitao Mao Zhikai Chen Wenzhuo Tang Jianan Zhao Yao Ma Tong Zhao Neil Shah Mikhail Galkin Jiliang Tang AI4CE 46 25 0 03 Feb 2024
Todyformer: Towards Holistic Dynamic Graph Transformers with Structure-Aware Tokenization Mahdi Biparva Raika Karimi Faezeh Faez Yingxue Zhang 28 3 0 02 Feb 2024
Graph-Mamba: Towards Long-Range Graph Sequence Modeling with Selective State Spaces Chloe X. Wang Oleksii Tsepa Jun Ma Bo Wang Mamba 25 85 0 01 Feb 2024
Graph Transformers without Positional Encodings Ayush Garg 14 0 0 31 Jan 2024
FedGT: Federated Node Classification with Scalable Graph Transformer Zaixin Zhang Qingyong Hu Yang Yu Weibo Gao Qi Liu FedML 33 2 0 26 Jan 2024
Design Your Own Universe: A Physics-Informed Agnostic Method for Enhancing Graph Neural Networks Dai Shi Andi Han Lequan Lin Yi Guo Zhiyong Wang Junbin Gao 21 8 0 26 Jan 2024
DeepRicci: Self-supervised Graph Structure-Feature Co-Refinement for Alleviating Over-squashing Li Sun Zhenhao Huang Hua Wu Junda Ye Hao Peng Zhengtao Yu Philip S. Yu 24 11 0 23 Jan 2024
Accurate and Scalable Estimation of Epistemic Uncertainty for Graph Neural Networks Puja Trivedi Mark Heimann Rushil Anirudh Danai Koutra Jayaraman J. Thiagarajan UQCV 24 4 0 07 Jan 2024
Motif-aware Riemannian Graph Neural Network with Generative-Contrastive Learning Li Sun Zhenhao Huang Zixi Wang Feiyang Wang Hao Peng Philip Yu 14 16 0 02 Jan 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 45 6 0 27 Dec 2023
NodeMixup: Tackling Under-Reaching for Graph Neural Networks Weigang Lu Ziyu Guan Wei Zhao Yaming Yang Long Jin 27 11 0 20 Dec 2023
Simplicial Representation Learning with Neural $k$ -Forms Kelly Maggs Celia Hacker Bastian Alexander Rieck AI4CE 25 10 0 13 Dec 2023
Curriculum-Enhanced Residual Soft An-Isotropic Normalization for Over-smoothness in Deep GNNs Jin Li Qirong Zhang Shuling Xu Xinlong Chen Longkun Guo Yanglan Fu 21 0 0 13 Dec 2023
The Graph Lottery Ticket Hypothesis: Finding Sparse, Informative Graph Structure Anton Tsitsulin Bryan Perozzi 24 5 0 08 Dec 2023
Large Language Models on Graphs: A Comprehensive Survey Bowen Jin Gang Liu Chi Han Meng-Long Jiang Heng Ji Jiawei Han AI4CE 24 135 0 05 Dec 2023
The Self-Loop Paradox: Investigating the Impact of Self-Loops on Graph Neural Networks Moritz Lampert Ingo Scholtes GNN SSL 17 4 0 04 Dec 2023
Recurrent Distance Filtering for Graph Representation Learning Yuhui Ding Antonio Orvieto Bobby He Thomas Hofmann GNN 27 6 0 03 Dec 2023
An Effective Universal Polynomial Basis for Spectral Graph Neural Networks Keke Huang Pietro Lió 16 1 0 30 Nov 2023
Over-Squashing in Riemannian Graph Neural Networks Julia Balla 16 0 0 27 Nov 2023
Effective Structural Encodings via Local Curvature Profiles Lukas Fesser Melanie Weber 19 3 0 24 Nov 2023
Exposition on over-squashing problem on GNNs: Current Methods, Benchmarks and Challenges Dai Shi Andi Han Lequan Lin Yi Guo Junbin Gao 47 11 0 13 Nov 2023
Mixture of Weak & Strong Experts on Graphs Hanqing Zeng Hanjia Lyu Diyi Hu Yinglong Xia Jiebo Luo 23 3 0 09 Nov 2023
Hybrid Focal and Full-Range Attention Based Graph Transformers Minhong Zhu Zhenhao Zhao Weiran Cai 25 0 0 08 Nov 2023
Sparse Training of Discrete Diffusion Models for Graph Generation Yiming Qin Clément Vignac Pascal Frossard 19 12 0 03 Nov 2023
Neural Atoms: Propagating Long-range Interaction in Molecular Graphs through Efficient Communication Channel Xuan Li Zhanke Zhou Jiangchao Yao Yu Rong Lu Zhang Bo Han 27 3 0 02 Nov 2023
Transformers as Graph-to-Graph Models James Henderson Alireza Mohammadshahi Andrei Catalin Coman Lesly Miculicich GNN 27 6 0 27 Oct 2023
Learning the dynamics of a one-dimensional plasma model with graph neural networks Diogo D Carvalho Diogo R Ferreira Luís O Silva AI4CE 8 0 0 26 Oct 2023
Graph Neural Networks with a Distribution of Parametrized Graphs See Hian Lee Feng Ji Kelin Xia Wee Peng Tay 31 0 0 25 Oct 2023
Neural Snowflakes: Universal Latent Graph Inference via Trainable Latent Geometries Haitz Sáez de Ocáriz Borde Anastasis Kratsios 24 4 0 23 Oct 2023
UniMAP: Universal SMILES-Graph Representation Learning Shikun Feng Lixin Yang Wei-Ying Ma Yanyan Lan OffRL 11 6 0 22 Oct 2023
From Continuous Dynamics to Graph Neural Networks: Neural Diffusion and Beyond Andi Han Dai Shi Lequan Lin Junbin Gao AI4CE GNN 35 20 0 16 Oct 2023
Mirage: Model-Agnostic Graph Distillation for Graph Classification Mridul Gupta S. Manchanda H. Kodamana Sayan Ranu DD 18 14 0 14 Oct 2023
Non-backtracking Graph Neural Networks Seonghyun Park Narae Ryu Ga-Rin Kim Dongyeop Woo Se-Young Yun Sungsoo Ahn 30 4 0 11 Oct 2023
Atom-Motif Contrastive Transformer for Molecular Property Prediction Wentao Yu Shuo Chen Chen Gong Gang Niu Masashi Sugiyama ViT 37 2 0 11 Oct 2023
Supercharging Graph Transformers with Advective Diffusion Qitian Wu Chenxiao Yang Kaipeng Zeng Fan Nie AI4CE 45 6 0 10 Oct 2023
On the Two Sides of Redundancy in Graph Neural Networks Vidya Sagar Sharma Samir Moustafa Johannes Langguth Wilfried N. Gansterer Nils M. Kriege 19 1 0 06 Oct 2023
Probabilistically Rewired Message-Passing Neural Networks Chendi Qian Andrei Manolache Kareem Ahmed Zhe Zeng Guy Van den Broeck Mathias Niepert Christopher Morris 31 12 0 03 Oct 2023
Transformers are efficient hierarchical chemical graph learners Zihan Pengmei Zimu Li Chih-chan Tien Risi Kondor Aaron R Dinner GNN 19 1 0 02 Oct 2023
Locality-Aware Graph-Rewiring in GNNs Federico Barbero A. Velingker Amin Saberi Michael M. Bronstein Francesco Di Giovanni 33 27 0 02 Oct 2023
Cooperative Graph Neural Networks Ben Finkelshtein Xingyue Huang Michael M. Bronstein .Ismail .Ilkan Ceylan GNN 22 19 0 02 Oct 2023
ResolvNet: A Graph Convolutional Network with multi-scale Consistency Christian Koke Abhishek Saroha Yuesong Shen Marvin Eisenberger Daniel Cremers GNN 22 1 0 30 Sep 2023
Mitigating Over-Smoothing and Over-Squashing using Augmentations of Forman-Ricci Curvature Lukas Fesser Melanie Weber 65 19 0 17 Sep 2023
Neural Latent Geometry Search: Product Manifold Inference via Gromov-Hausdorff-Informed Bayesian Optimization Haitz Sáez de Ocáriz Borde Alvaro Arroyo Ismael Morales Ingmar Posner Xiaowen Dong 12 9 0 09 Sep 2023
Curve Your Attention: Mixed-Curvature Transformers for Graph Representation Learning Sungjun Cho Seunghyuk Cho Sungwoo Park Hankook Lee Ho Hin Lee Moontae Lee 20 6 0 08 Sep 2023