DropGNN: Random Dropouts Increase the Expressiveness of Graph Neural Networks

11 November 2021

Roger Wattenhofer

Papers citing "DropGNN: Random Dropouts Increase the Expressiveness of Graph Neural Networks"

48 / 98 papers shown

Title
Provably Powerful Graph Neural Networks for Directed Multigraphs Béni Egressy Luc von Niederhäusern Jovan Blanusa Erik Altman Roger Wattenhofer Kubilay Atasu 25 15 0 20 Jun 2023
Path Neural Networks: Expressive and Accurate Graph Neural Networks Gaspard Michel Giannis Nikolentzos J. Lutzeyer Michalis Vazirgiannis GNN 18 26 0 09 Jun 2023
BeMap: Balanced Message Passing for Fair Graph Neural Network Xiao Lin Jian Kang Weilin Cong Hanghang Tong MoE 37 6 0 07 Jun 2023
Extending the Design Space of Graph Neural Networks by Rethinking Folklore Weisfeiler-Lehman Jiarui Feng Lecheng Kong Hao Liu Dacheng Tao Fuhai Li Muhan Zhang Yixin Chen 44 10 0 05 Jun 2023
Union Subgraph Neural Networks Jiaxing Xu Aihu Zhang Qingtian Bian Vijay Prakash Dwivedi Yiping Ke GNN 27 6 0 25 May 2023
Robust Ante-hoc Graph Explainer using Bilevel Optimization Kha-Dinh Luong Mert Kosan A. Silva Ambuj K. Singh 34 6 0 25 May 2023
DRew: Dynamically Rewired Message Passing with Delay Benjamin Gutteridge Xiaowen Dong Michael M. Bronstein Francesco Di Giovanni 36 58 0 13 May 2023
What Do GNNs Actually Learn? Towards Understanding their Representations Giannis Nikolentzos Michail Chatzianastasis Michalis Vazirgiannis GNN AI4CE 13 0 0 21 Apr 2023
An Empirical Study of Realized GNN Expressiveness Yanbo Wang Muhan Zhang 42 10 0 16 Apr 2023
Counterfactual Learning on Graphs: A Survey Zhimeng Guo Teng Xiao Zongyu Wu Charu C. Aggarwal Hui Liu Suhang Wang CML AI4CE 40 19 0 03 Apr 2023
An Efficient Subgraph GNN with Provable Substructure Counting Power Zuoyu Yan Junru Zhou Liangcai Gao Zhi Tang Muhan Zhang GNN 29 12 0 19 Mar 2023
NESS: Node Embeddings from Static SubGraphs Talip Uçar 23 1 0 15 Mar 2023
MulGT: Multi-task Graph-Transformer with Task-aware Knowledge Injection and Domain Knowledge-driven Pooling for Whole Slide Image Analysis Weiqin Zhao Shujun Wang Maximus C. F. Yeung Tianye Niu Lequan Yu 44 9 0 21 Feb 2023
WL meet VC Christopher Morris Floris Geerts Jan Tonshoff Martin Grohe 38 27 0 26 Jan 2023
Boosting the Cycle Counting Power of Graph Neural Networks with I $^2$ -GNNs Yinan Huang Xingang Peng Jianzhu Ma Muhan Zhang 84 47 0 22 Oct 2022
Towards Accurate Subgraph Similarity Computation via Neural Graph Pruning Linfeng Liu Xuhong Han Dawei Zhou Liping Liu 35 5 0 19 Oct 2022
On the Effectiveness of Hybrid Pooling in Mixup-Based Graph Learning for Language Processing Zeming Dong Qiang Hu Zhenya Zhang Yuejun Guo Maxime Cordy Mike Papadakis Yves Le Traon Jianjun Zhao 29 3 0 06 Oct 2022
Graph Classification via Discriminative Edge Feature Learning Yang Yi Xuequan Lu Shang Gao A. Robles-Kelly Yuejie Zhang GNN 34 7 0 05 Oct 2022
Hierarchical Graph Pooling is an Effective Citywide Traffic Condition Prediction Model Shilin Pu Liang Chu Zhuoran Hou Jincheng Hu Yanjun Huang Yuanjian Zhang 219 0 0 08 Sep 2022
A Class-Aware Representation Refinement Framework for Graph Classification Jiaxing Xu Jinjie Ni Yiping Ke GNN 29 4 0 02 Sep 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
A Topological characterisation of Weisfeiler-Leman equivalence classes Jacob Bamberger GNN 19 3 0 23 Jun 2022
Ordered Subgraph Aggregation Networks Chao Qian Gaurav Rattan Floris Geerts Christopher Morris Mathias Niepert 41 57 0 22 Jun 2022
Understanding and Extending Subgraph GNNs by Rethinking Their Symmetries Fabrizio Frasca Beatrice Bevilacqua Michael M. Bronstein Haggai Maron 37 125 0 22 Jun 2022
Agent-based Graph Neural Networks Karolis Martinkus Pál András Papp Benedikt Schesch Roger Wattenhofer LLMAG GNN 29 17 0 22 Jun 2022
DiffWire: Inductive Graph Rewiring via the Lovász Bound Adrián Arnaiz-Rodríguez Ahmed Begga Francisco Escolano Nuria Oliver 29 62 0 15 Jun 2022
Universally Expressive Communication in Multi-Agent Reinforcement Learning Matthew Morris Thomas D. Barrett Arnu Pretorius 24 4 0 14 Jun 2022
Fundamental Limits in Formal Verification of Message-Passing Neural Networks Marco Salzer M. Lange GNN 11 10 0 10 Jun 2022
Empowering GNNs via Edge-Aware Weisfeiler-Leman Algorithm Meng Liu Haiyang Yu Shuiwang Ji 33 1 0 04 Jun 2022
Graph Neural Networks with Precomputed Node Features Béni Egressy Roger Wattenhofer 17 2 0 01 Jun 2022
Template based Graph Neural Network with Optimal Transport Distances Cédric Vincent-Cuaz Rémi Flamary Marco Corneli Titouan Vayer Nicolas Courty OT 43 20 0 31 May 2022
Asynchronous Neural Networks for Learning in Graphs Lukas Faber Roger Wattenhofer GNN 14 3 0 24 May 2022
A Survey of Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection Bingzhe Wu Jintang Li Junchi Yu Yatao Bian Hengtong Zhang ... Guangyu Sun Peng Cui Zibin Zheng Zhe Liu P. Zhao OOD 37 25 0 20 May 2022
Unified GCNs: Towards Connecting GCNs with CNNs Ziyan Zhang Bo Jiang Bin Luo GNN 25 1 0 26 Apr 2022
DropMessage: Unifying Random Dropping for Graph Neural Networks Taoran Fang Zhiqing Xiao Chunping Wang Jiarong Xu Xuan Yang Yang Yang 16 46 0 21 Apr 2022
Graph Pooling for Graph Neural Networks: Progress, Challenges, and Opportunities Chuang Liu Yibing Zhan Jia Wu Chang Li Bo Du Wenbin Hu Tongliang Liu Dacheng Tao GNN AI4CE 30 80 0 15 Apr 2022
A Survey on Graph Representation Learning Methods Shima Khoshraftar A. An GNN AI4TS 27 108 0 04 Apr 2022
SPECTRE: Spectral Conditioning Helps to Overcome the Expressivity Limits of One-shot Graph Generators Karolis Martinkus Andreas Loukas Nathanael Perraudin Roger Wattenhofer 36 67 0 04 Apr 2022
SpeqNets: Sparsity-aware Permutation-equivariant Graph Networks Christopher Morris Gaurav Rattan Sandra Kiefer Siamak Ravanbakhsh 50 40 0 25 Mar 2022
Sign and Basis Invariant Networks for Spectral Graph Representation Learning Derek Lim Joshua Robinson Lingxiao Zhao Tess E. Smidt S. Sra Haggai Maron Stefanie Jegelka 49 141 0 25 Feb 2022
Message passing all the way up Petar Velickovic 111 63 0 22 Feb 2022
1-WL Expressiveness Is (Almost) All You Need Markus Zopf 19 11 0 21 Feb 2022
Recent Advances in Reliable Deep Graph Learning: Inherent Noise, Distribution Shift, and Adversarial Attack Jintang Li Bingzhe Wu Chengbin Hou Guoji Fu Yatao Bian Liang Chen Junzhou Huang Zibin Zheng OOD AAML 32 6 0 15 Feb 2022
A Theoretical Comparison of Graph Neural Network Extensions Pál András Papp Roger Wattenhofer 100 46 0 30 Jan 2022
Towards Quantum Graph Neural Networks: An Ego-Graph Learning Approach Xing Ai Zhihong Zhang Luzhe Sun Junchi Yan Edwin R. Hancock GNN 39 11 0 13 Jan 2022
Weisfeiler and Leman go Machine Learning: The Story so far Christopher Morris Y. Lipman Haggai Maron Bastian Alexander Rieck Nils M. Kriege Martin Grohe Matthias Fey Karsten M. Borgwardt GNN 43 111 0 18 Dec 2021
Representation Learning on Graphs with Jumping Knowledge Networks Keyulu Xu Chengtao Li Yonglong Tian Tomohiro Sonobe Ken-ichi Kawarabayashi Stefanie Jegelka GNN 267 1,945 0 09 Jun 2018
MoleculeNet: A Benchmark for Molecular Machine Learning Zhenqin Wu Bharath Ramsundar Evan N. Feinberg Joseph Gomes C. Geniesse Aneesh S. Pappu K. Leswing Vijay S. Pande OOD 175 1,778 0 02 Mar 2017