MotifNet: a motif-based Graph Convolutional Network for directed graphs

4 February 2018

Papers citing "MotifNet: a motif-based Graph Convolutional Network for directed graphs"

26 / 26 papers shown

Title
Understanding the Design Principles of Link Prediction in Directed Settings Jun Zhai Muberra Ozmen Thomas Markovich AI4CE 33 0 0 24 Feb 2025
Graph Neural Networks for Edge Signals: Orientation Equivariance and Invariance Dominik Fuchsgruber Tim Poštuvan Stephan Günnemann Simon Geisler 39 2 0 22 Oct 2024
A Benchmark on Directed Graph Representation Learning in Hardware Designs Haoyu Wang Yinan Huang Nan Wu Pan Li OOD 40 1 0 09 Oct 2024
On Structural Expressive Power of Graph Transformers Wenhao Zhu Tianyu Wen Guojie Song Liangji Wang Bo Zheng 25 15 0 23 May 2023
Edge Directionality Improves Learning on Heterophilic Graphs Emanuele Rossi Bertrand Charpentier Francesco Di Giovanni Fabrizio Frasca Stephan Günnemann Michael M. Bronstein 22 56 0 17 May 2023
MPool: Motif-Based Graph Pooling Muhammad Ifte Khairul Islam Max Khanov Esra Akbas 19 4 0 07 Mar 2023
Make Heterophily Graphs Better Fit GNN: A Graph Rewiring Approach Wendong Bi Lun Du Qiang Fu Yanlin Wang Shi Han Dongmei Zhang 22 27 0 17 Sep 2022
An Explainer for Temporal Graph Neural Networks Wenchong He Minh Nhat Vu Zhe Jiang My T. Thai AI4TS 9 17 0 02 Sep 2022
MSGNN: A Spectral Graph Neural Network Based on a Novel Magnetic Signed Laplacian Yixuan He Michael Perlmutter G. Reinert Mihai Cucuringu 30 27 0 01 Sep 2022
NAFS: A Simple yet Tough-to-beat Baseline for Graph Representation Learning Wentao Zhang Zeang Sheng Mingyu Yang Yang Li Yu Shen Zhi-Xin Yang Bin Cui AAML 18 16 0 17 Jun 2022
Theory of Graph Neural Networks: Representation and Learning Stefanie Jegelka GNN AI4CE 33 68 0 16 Apr 2022
PaSca: a Graph Neural Architecture Search System under the Scalable Paradigm Wentao Zhang Yu Shen Zheyu Lin Yang Li Xiaosen Li Wenbin Ouyang Yangyu Tao Zhi-Xin Yang Bin Cui GNN 29 59 0 01 Mar 2022
Directed Graph Auto-Encoders Georgios Kollias Vasileios Kalantzis Tsuyoshi Idé A. Lozano Naoki Abe BDL GNN 28 34 0 25 Feb 2022
Understanding over-squashing and bottlenecks on graphs via curvature Jake Topping Francesco Di Giovanni B. Chamberlain Xiaowen Dong M. Bronstein 41 425 0 29 Nov 2021
Asymmetric Graph Representation Learning Zhuo Tan B. Liu Guosheng Yin 24 1 0 14 Oct 2021
From Stars to Subgraphs: Uplifting Any GNN with Local Structure Awareness Lingxiao Zhao Wei Jin L. Akoglu Neil Shah GNN 24 160 0 07 Oct 2021
GMLP: Building Scalable and Flexible Graph Neural Networks with Feature-Message Passing Wentao Zhang Yu Shen Zheyu Lin Yang Li Xiaosen Li Wenbin Ouyang Yangyu Tao Zhi-Xin Yang Bin Cui 19 9 0 20 Apr 2021
PGM-Explainer: Probabilistic Graphical Model Explanations for Graph Neural Networks Minh Nhat Vu My T. Thai BDL 8 327 0 12 Oct 2020
Graph signal processing for machine learning: A review and new perspectives Xiaowen Dong D. Thanou Laura Toni M. Bronstein P. Frossard 19 153 0 31 Jul 2020
Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting Giorgos Bouritsas Fabrizio Frasca S. Zafeiriou M. Bronstein 46 423 0 16 Jun 2020
Motif-Based Spectral Clustering of Weighted Directed Networks W. Underwood Andrew Elliott Mihai Cucuringu 16 12 0 02 Apr 2020
Can Graph Neural Networks Count Substructures? Zhengdao Chen Lei Chen Soledad Villar Joan Bruna GNN 54 319 0 10 Feb 2020
Graph Neural Networks for IceCube Signal Classification Nicholas Choma Federico Monti Lisa Gerhardt T. Palczewski Z. Ronaghi P. Prabhat W. Bhimji M. Bronstein S. Klein Joan Bruna 13 76 0 17 Sep 2018
PeerNets: Exploiting Peer Wisdom Against Adversarial Attacks Jan Svoboda Jonathan Masci Federico Monti M. Bronstein Leonidas J. Guibas AAML GNN 33 41 0 31 May 2018
Geometric deep learning on graphs and manifolds using mixture model CNNs Federico Monti Davide Boscaini Jonathan Masci Emanuele Rodolà Jan Svoboda M. Bronstein GNN 251 1,811 0 25 Nov 2016
Geometric deep learning: going beyond Euclidean data M. Bronstein Joan Bruna Yann LeCun Arthur Szlam P. Vandergheynst GNN 247 3,236 0 24 Nov 2016