Garnet: Reduced-rank topology learning for robust and scalable graph neural networks

C Deng, X Li, Z Feng, Z Zhang - Learning on Graphs …, 2022 - proceedings.mlr.press
Graph neural networks (GNNs) have been increasingly deployed in various applications that
involve learning on non-Euclidean data. However, recent studies show that GNNs are …
被引用次数：16 相关文章

GARNET: Reduced-Rank Topology Learning for Robust and Scalable Graph Neural Networks

C Deng, X Li, Z Feng, Z Zhang - The First Learning on Graphs Conference - openreview.net
Graph neural networks (GNNs) have been increasingly deployed in various applications that
involve learning on non-Euclidean data. However, recent studies show that GNNs are …
[PDF] cornell.edu

[PDF][PDF] GARNET: Reduced-Rank Topology Learning for Robust and Scalable Graph Neural Networks

C Deng, X Li, Z Feng, Z Zhang - csl.cornell.edu
Graph neural networks (GNNs) have been increasingly deployed in various applications that
involve learning on non-Euclidean data. However, recent studies show that GNNs are …

GARNET: REDUCED-RANK TOPOLOGY LEARNING FOR ROBUST AND SCALABLE GRAPH NEURAL NETWORKS

Z Zhang - 2022 - zepengzhang.com
GNNs are vulnerable to adversarial structural attacks. Previous low-rank approximation
defense methods eliminate high-rank adversarial components to improve the robustness …

GARNET: Reduced-Rank Topology Learning for Robust and Scalable Graph Neural Networks

C Deng, X Li, Z Feng, Z Zhang - arXiv e-prints, 2022 - ui.adsabs.harvard.edu
Graph neural networks (GNNs) have been increasingly deployed in various applications that
involve learning on non-Euclidean data. However, recent studies show that GNNs are …
[PDF] nsf.gov

[PDF][PDF] GARNET: Reduced-Rank Topology Learning for Robust and Scalable Graph Neural Networks

C Deng, X Li - Proceedings of the First Learning on Graphs …, 2022 - par.nsf.gov
Graph neural networks (GNNs) have been increasingly deployed in various applications that
involve learning on non-Euclidean data. However, recent studies show that GNNs are …

GARNET: Reduced-Rank Topology Learning for Robust and Scalable Graph Neural Networks

C Deng, X Li, Z Feng, Z Zhang - arXiv preprint arXiv:2201.12741, 2022 - arxiv.org
Graph neural networks (GNNs) have been increasingly deployed in various applications that
involve learning on non-Euclidean data. However, recent studies show that GNNs are …
[PDF] nsf.gov

[PDF][PDF] GARNET: Reduced-Rank Topology Learning for Robust and Scalable Graph Neural Networks

C Deng, X Li, Z Feng, Z Zhang - Learning on Graphs Conference, 2022 - par.nsf.gov
Graph neural networks (GNNs) have been increasingly deployed in various applications that
involve learning on non-Euclidean data. However, recent studies show that GNNs are …