Transferability of Spectral Graph Convolutional Neural Networks

30 July 2019

Papers citing "Transferability of Spectral Graph Convolutional Neural Networks"

50 / 87 papers shown

Title
Towards Graph Foundation Models: Learning Generalities Across Graphs via Task-Trees Zehong Wang Zheyuan Zhang Tianyi Ma Nitesh V. Chawla Chuxu Zhang Yanfang Ye AI4CE 66 0 0 21 Dec 2024
GFT: Graph Foundation Model with Transferable Tree Vocabulary Zehong Wang Zheyuan Zhang Nitesh V. Chawla Chuxu Zhang Yanfang Ye 29 9 0 09 Nov 2024
Graph neural networks and non-commuting operators Mauricio Velasco Kaiying O'Hare Bernardo Rychtenberg Soledad Villar GNN 38 0 0 06 Nov 2024
A Review of Graph-Powered Data Quality Applications for IoT Monitoring Sensor Networks Pau Ferrer-Cid Jose M. Barcelo-Ordinas J. García-Vidal 37 2 0 28 Oct 2024
Sparse Covariance Neural Networks Andrea Cavallo Zhan Gao Elvin Isufi 16 0 0 02 Oct 2024
Generalization of Graph Neural Networks is Robust to Model Mismatch Zhiyang Wang J. Cerviño Alejandro Ribeiro 24 1 0 25 Aug 2024
A Manifold Perspective on the Statistical Generalization of Graph Neural Networks Zhiyang Wang J. Cerviño Alejandro Ribeiro AI4CE GNN 18 5 0 07 Jun 2024
Equivariant Machine Learning on Graphs with Nonlinear Spectral Filters Y. Lin Ronen Talmon Ron Levie 26 0 0 03 Jun 2024
Transfer Learning Under High-Dimensional Graph Convolutional Regression Model for Node Classification Jiachen Chen Danyang Huang Liyuan Wang Kathryn L. Lunetta Debarghya Mukherjee Huimin Cheng 17 0 0 26 May 2024
Generalization Bounds for Message Passing Networks on Mixture of Graphons Sohir Maskey Gitta Kutyniok Ron Levie 48 4 0 04 Apr 2024
Subgraph Pooling: Tackling Negative Transfer on Graphs Zehong Wang Zheyuan Zhang Chuxu Zhang Yanfang Ye 26 6 0 14 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 27 4 0 03 Feb 2024
Stability of Graph Convolutional Neural Networks through the lens of small perturbation analysis Lucia Testa Claudio Battiloro S. Sardellitti Sergio Barbarossa AAML 14 4 0 20 Dec 2023
Robust Graph Neural Network based on Graph Denoising Victor M. Tenorio Samuel Rey Antonio G. Marques AAML 11 1 0 11 Dec 2023
On the Trade-Off between Stability and Representational Capacity in Graph Neural Networks Zhan Gao Amanda Prorok Elvin Isufi 16 1 0 04 Dec 2023
A Local Graph Limits Perspective on Sampling-Based GNNs Yeganeh Alimohammadi Luana Ruiz Amin Saberi 19 2 0 17 Oct 2023
HoloNets: Spectral Convolutions do extend to Directed Graphs Christian Koke Daniel Cremers 23 8 0 03 Oct 2023
ResolvNet: A Graph Convolutional Network with multi-scale Consistency Christian Koke Abhishek Saroha Yuesong Shen Marvin Eisenberger Daniel Cremers GNN 17 1 0 30 Sep 2023
Generalized Graphon Process: Convergence of Graph Frequencies in Stretched Cut Distance Xingchao Jian Feng Ji Wee Peng Tay 11 2 0 11 Sep 2023
Approximately Equivariant Graph Networks Ningyuan Huang Ron Levie Soledad Villar 16 18 0 21 Aug 2023
Transferability of Graph Neural Networks using Graphon and Sampling Theories A. Neuman J. Bramburger 9 1 0 25 Jul 2023
Limits, approximation and size transferability for GNNs on sparse graphs via graphops Thien Le Stefanie Jegelka 11 10 0 07 Jun 2023
Geometric Graph Filters and Neural Networks: Limit Properties and Discriminability Trade-offs Zhiyang Wang Luana Ruiz Alejandro Ribeiro GNN 26 6 0 29 May 2023
A graphon-signal analysis of graph neural networks Ron Levie 10 16 0 25 May 2023
Size Generalization of Graph Neural Networks on Biological Data: Insights and Practices from the Spectral Perspective Gao Li Danai Koutra Yujun Yan 13 1 0 24 May 2023
What functions can Graph Neural Networks compute on random graphs? The role of Positional Encoding Nicolas Keriven Samuel Vaiter 23 8 0 24 May 2023
Convergence of Message Passing Graph Neural Networks with Generic Aggregation On Large Random Graphs Matthieu Cordonnier Nicolas Keriven Nicolas M Tremblay Samuel Vaiter GNN 45 7 0 21 Apr 2023
When to Pre-Train Graph Neural Networks? From Data Generation Perspective! Yu Cao Jiarong Xu Carl Yang Jiaan Wang Yunchao Zhang Chunping Wang L. Chen Yang Yang 8 16 0 29 Mar 2023
Tangent Bundle Convolutional Learning: from Manifolds to Cellular Sheaves and Back Claudio Battiloro Zhiyang Wang Hans Riess P. Di Lorenzo Alejandro Ribeiro 15 9 0 20 Mar 2023
A Survey on Spectral Graph Neural Networks Deyu Bo Xiao Wang Yang Liu Yuan Fang Yawen Li Chuan Shi 19 24 0 11 Feb 2023
Zero-One Laws of Graph Neural Networks Sam Adam-Day Theodor-Mihai Iliant .Ismail .Ilkan Ceylan GNN AI4CE 11 3 0 30 Jan 2023
Limitless stability for Graph Convolutional Networks Christian Koke 30 2 0 26 Jan 2023
Graph Neural Tangent Kernel: Convergence on Large Graphs Sanjukta Krishnagopal Luana Ruiz 14 7 0 25 Jan 2023
State of the Art and Potentialities of Graph-level Learning Zhenyu Yang Ge Zhang Jia Wu Jian Yang Quan.Z Sheng ... Charu C. Aggarwal Hao Peng Wenbin Hu Edwin R. Hancock Pietro Lio' GNN AI4CE 24 10 0 14 Jan 2023
Learning Stable Graph Neural Networks via Spectral Regularization Zhan Gao Elvin Isufi 10 3 0 13 Nov 2022
Stable and Transferable Hyper-Graph Neural Networks Mikhail Hayhoe Hans Riess V. Preciado Alejandro Ribeiro 35 1 0 11 Nov 2022
Space-Time Graph Neural Networks with Stochastic Graph Perturbations Samar Hadou Charilaos I. Kanatsoulis Alejandro Ribeiro 16 4 0 28 Oct 2022
Tangent Bundle Filters and Neural Networks: from Manifolds to Cellular Sheaves and Back Claudio Battiloro Zhiyang Wang Hans Riess P. Lorenzo Alejandro Ribeiro 29 13 0 26 Oct 2022
Unveiling the Sampling Density in Non-Uniform Geometric Graphs Raffaele Paolino Aleksandar Bojchevski Stephan Günnemann Gitta Kutyniok Ron Levie 23 2 0 15 Oct 2022
Convolutional Neural Networks on Manifolds: From Graphs and Back Zhiyang Wang Luana Ruiz Alejandro Ribeiro 3DPC GNN 32 14 0 01 Oct 2022
MSGNN: A Spectral Graph Neural Network Based on a Novel Magnetic Signed Laplacian Yixuan He Michael Perlmutter G. Reinert Mihai Cucuringu 14 27 0 01 Sep 2022
MentorGNN: Deriving Curriculum for Pre-Training GNNs Dawei Zhou Lecheng Zheng Dongqi Fu Jiawei Han Jingrui He 14 22 0 21 Aug 2022
Graph-Time Convolutional Neural Networks: Architecture and Theoretical Analysis Mohammad Sabbaqi Elvin Isufi GNN AI4TS 17 13 0 30 Jun 2022
The Manifold Scattering Transform for High-Dimensional Point Cloud Data Joyce A. Chew H. Steach Siddharth Viswanath Hau‐Tieng Wu M. Hirn Deanna Needell Smita Krishnaswamy Michael Perlmutter 3DPC 14 12 0 21 Jun 2022
Generalised Implicit Neural Representations Daniele Grattarola P. Vandergheynst 9 30 0 31 May 2022
OOD Link Prediction Generalization Capabilities of Message-Passing GNNs in Larger Test Graphs Yangze Zhou Gitta Kutyniok Bruno Ribeiro OODD AI4CE 70 37 0 30 May 2022
Not too little, not too much: a theoretical analysis of graph (over)smoothing Nicolas Keriven 15 88 0 24 May 2022
Representation Power of Graph Neural Networks: Improved Expressivity via Algebraic Analysis Charilaos I. Kanatsoulis Alejandro Ribeiro 17 4 0 19 May 2022
Unified GCNs: Towards Connecting GCNs with CNNs Ziyan Zhang Bo Jiang Bin Luo GNN 12 1 0 26 Apr 2022
Graph Neural Network based Agent in Google Research Football Yizhan Niu Jinglong Liu Yuhao Shi Jiren Zhu GNN 13 2 0 23 Apr 2022