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On the Bottleneck of Graph Neural Networks and its Practical Implications

9 June 2020

Uri Alon

Eran Yahav

GNN

ArXiv (abs)PDF HTML Github (94★)

Papers citing "On the Bottleneck of Graph Neural Networks and its Practical Implications"

50 / 416 papers shown

Title
The Self-Loop Paradox: Investigating the Impact of Self-Loops on Graph Neural Networks Moritz Lampert Ingo Scholtes GNN SSL 56 3 0 04 Dec 2023
Recurrent Distance Filtering for Graph Representation Learning Yuhui Ding Antonio Orvieto Bobby He Thomas Hofmann GNN 136 8 0 03 Dec 2023
Improving embedding of graphs with missing data by soft manifolds Andrea Marinoni Pietro Lio Alessandro Barp Christian Jutten Mark Girolami 70 0 0 29 Nov 2023
Over-Squashing in Riemannian Graph Neural Networks Julia Balla 72 1 0 27 Nov 2023
Effective Structural Encodings via Local Curvature Profiles Lukas Fesser Melanie Weber 85 3 0 24 Nov 2023
Learning to Optimise Wind Farms with Graph Transformers Siyi Li Arnaud Robert A. A. Faisal M. Piggott 45 5 0 21 Nov 2023
Content Augmented Graph Neural Networks Fatemeh Gholamzadeh Nasrabadi AmirHossein Kashani Pegah Zahedi M. H. Chehreghani 68 3 0 21 Nov 2023
AMES: A Differentiable Embedding Space Selection Framework for Latent Graph Inference Yuan Lu Haitz Sáez de Ocáriz Borde Pietro Lio 80 2 0 20 Nov 2023
Higher-Order Expander Graph Propagation Thomas Christie Yu He 76 4 0 14 Nov 2023
Exposition on over-squashing problem on GNNs: Current Methods, Benchmarks and Challenges Dai Shi Andi Han Lequan Lin Yi Guo Junbin Gao 123 14 0 13 Nov 2023
Multiscale Neural Operators for Solving Time-Independent PDEs Winfried Ripken Lisa Coiffard Felix Pieper Sebastian Dziadzio AI4CE 57 2 0 10 Nov 2023
Mixture of Weak & Strong Experts on Graphs Hanqing Zeng Hanjia Lyu Diyi Hu Yinglong Xia Jiebo Luo 95 4 0 09 Nov 2023
Hybrid Focal and Full-Range Attention Based Graph Transformers Minhong Zhu Zhenhao Zhao Weiran Cai 72 0 0 08 Nov 2023
Sparse Training of Discrete Diffusion Models for Graph Generation Yiming Qin Clément Vignac Pascal Frossard 76 14 0 03 Nov 2023
Sliced Denoising: A Physics-Informed Molecular Pre-Training Method Yuyan Ni Shikun Feng Wei-Ying Ma Zhiming Ma Yanyan Lan DiffM AI4CE 82 11 0 03 Nov 2023
A Graph-to-Text Approach to Knowledge-Grounded Response Generation in Human-Robot Interaction Nicholas Walker Stefan Ultes Pierre Lison LM&Ro 159 1 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 118 5 0 02 Nov 2023
Diversified Node Sampling based Hierarchical Transformer Pooling for Graph Representation Learning Gaichao Li Jinsong Chen John E. Hopcroft Kun He 46 0 0 31 Oct 2023
Transformers as Graph-to-Graph Models James Henderson Alireza Mohammadshahi Andrei Catalin Coman Lesly Miculicich GNN 69 6 0 27 Oct 2023
Multi-omics Sampling-based Graph Transformer for Synthetic Lethality Prediction Xusheng Zhao Hao Liu Qiong Dai Hao Peng Xu Bai Huailiang Peng 46 2 0 17 Oct 2023
SignGT: Signed Attention-based Graph Transformer for Graph Representation Learning Jinsong Chen Gaichao Li John E. Hopcroft Kun He SLR 88 5 0 17 Oct 2023
From Continuous Dynamics to Graph Neural Networks: Neural Diffusion and Beyond Andi Han Dai Shi Lequan Lin Junbin Gao AI4CE GNN 105 24 0 16 Oct 2023
Non-backtracking Graph Neural Networks Seonghyun Park Narae Ryu Ga-Rin Kim Dongyeop Woo Se-Young Yun SungSoo Ahn 84 4 0 11 Oct 2023
Are GATs Out of Balance? Nimrah Mustafa Aleksandar Bojchevski R. Burkholz 130 5 0 11 Oct 2023
Flood and Echo Net: Algorithmically Aligned GNNs that Generalize Joël Mathys Florian Grötschla K. Nadimpalli Roger Wattenhofer FedML 84 0 0 10 Oct 2023
Tailoring Self-Attention for Graph via Rooted Subtrees Siyuan Huang Yunchong Song Jiayue Zhou Zhouhan Lin 81 8 0 08 Oct 2023
Latent Graph Inference with Limited Supervision Jianglin Lu Yi Tian Xu Huan Wang Yue Bai Yun Fu 71 4 0 06 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 84 2 0 06 Oct 2023
Fishnets: Information-Optimal, Scalable Aggregation for Sets and Graphs T. Lucas Makinen Justin Alsing Benjamin Dan Wandelt GNN FedML 65 3 0 05 Oct 2023
Probabilistically Rewired Message-Passing Neural Networks Chendi Qian Andrei Manolache Kareem Ahmed Zhe Zeng Guy Van den Broeck Mathias Niepert Christopher Morris 150 15 0 03 Oct 2023
Transformers are efficient hierarchical chemical graph learners Zihan Pengmei Zimu Li Chih-chan Tien Risi Kondor Aaron R Dinner GNN 48 2 0 02 Oct 2023
Locality-Aware Graph-Rewiring in GNNs Federico Barbero A. Velingker Amin Saberi Michael M. Bronstein Francesco Di Giovanni 108 33 0 02 Oct 2023
Cooperative Graph Neural Networks Ben Finkelshtein Xingyue Huang Michael M. Bronstein .Ismail .Ilkan Ceylan GNN 110 26 0 02 Oct 2023
ResolvNet: A Graph Convolutional Network with multi-scale Consistency Christian Koke Abhishek Saroha Yuesong Shen Marvin Eisenberger Daniel Cremers GNN 54 1 0 30 Sep 2023
Deep Prompt Tuning for Graph Transformers Reza Shirkavand Heng-Chiao Huang 57 7 0 18 Sep 2023
Mitigating Over-Smoothing and Over-Squashing using Augmentations of Forman-Ricci Curvature Lukas Fesser Melanie Weber 100 25 0 17 Sep 2023
Motif-aware Attribute Masking for Molecular Graph Pre-training Eric Inae Gang Liu Meng Jiang AI4CE 122 14 0 08 Sep 2023
Graph Neural Networks Use Graphs When They Shouldn't Maya Bechler-Speicher Ido Amos Ran Gilad-Bachrach Amir Globerson GNN AI4CE 45 15 0 08 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 111 7 0 08 Sep 2023
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 79 12 0 06 Sep 2023
Hierarchical Grammar-Induced Geometry for Data-Efficient Molecular Property Prediction Minghao Guo Veronika Thost Samuel W Song A. Balachandran Payel Das Jie Chen Wojciech Matusik AI4CE 71 0 0 04 Sep 2023
Curvature-based Pooling within Graph Neural Networks Cedric Sanders Andreas Roth Thomas Liebig 80 5 0 31 Aug 2023
TransGNN: Harnessing the Collaborative Power of Transformers and Graph Neural Networks for Recommender Systems Peiyan Zhang Yuchen Yan Xi Zhang Chaozhuo Li Senzhang Wang Feiran Huang Sunghun Kim 79 22 0 28 Aug 2023
Enhancing Graph Transformers with Hierarchical Distance Structural Encoding Yuan Luo Hongkang Li Lei Shi Xiao-Ming Wu 78 8 0 22 Aug 2023
Investigating the Interplay between Features and Structures in Graph Learning Daniele Castellana Federico Errica 101 4 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 97 23 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 231 26 0 16 Aug 2023
Label Inference Attacks against Node-level Vertical Federated GNNs Marco Arazzi Mauro Conti Stefanos Koffas Marina Krček Antonino Nocera S. Picek Jing Xu FedML AAML 55 1 0 04 Aug 2023
Graph Neural Networks for Forecasting Multivariate Realized Volatility with Spillover Effects Chao Zhang Xingyue Pu Ning Zhang Xiaowen Dong 24 4 0 01 Aug 2023
Feature Transportation Improves Graph Neural Networks Moshe Eliasof E. Haber Eran Treister GNN 109 12 0 29 Jul 2023