How Powerful is Implicit Denoising in Graph Neural Networks

29 September 2022

Papers citing "How Powerful is Implicit Denoising in Graph Neural Networks"

7 / 7 papers shown

Title
Joint Graph Rewiring and Feature Denoising via Spectral Resonance Jonas Linkerhagner Cheng Shi Ivan Dokmanić 145 0 0 13 Aug 2024
Graph Neural Networks Inspired by Classical Iterative Algorithms Yongyi Yang T. Liu Yangkun Wang Jinjing Zhou Quan Gan Zhewei Wei Zheng Zhang Zengfeng Huang David Wipf 56 82 0 10 Mar 2021
Simple and Deep Graph Convolutional Networks Ming Chen Zhewei Wei Zengfeng Huang Bolin Ding Yaliang Li GNN 95 1,473 0 04 Jul 2020
Open Graph Benchmark: Datasets for Machine Learning on Graphs Weihua Hu Matthias Fey Marinka Zitnik Yuxiao Dong Hongyu Ren Bowen Liu Michele Catasta J. Leskovec 254 2,701 0 02 May 2020
Certifiable Robustness and Robust Training for Graph Convolutional Networks Daniel Zügner Stephan Günnemann OffRL 70 162 0 28 Jun 2019
Adversarial Attacks on Graph Neural Networks via Meta Learning Daniel Zügner Stephan Günnemann OOD AAML GNN 123 569 0 22 Feb 2019
N-GCN: Multi-scale Graph Convolution for Semi-supervised Node Classification Sami Abu-El-Haija Amol Kapoor Bryan Perozzi Joonseok Lee GNN SSL 63 259 0 24 Feb 2018