【HGNN】AAAI 2022 RoHe Robust Heterogeneous Graph Neural Networks against Adversarial Attacks - 代码天地

【HGNN】AAAI 2022 RoHe Robust Heterogeneous Graph Neural Networks against Adversarial Attacks

企业开发 2022-09-05 01:59:06 阅读次数: 0

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转载自blog.csdn.net/lj2048/article/details/126380159

【HGNN】AAAI 2022 RoHe Robust Heterogeneous Graph Neural Networks against Adversarial Attacks

【随记】Adversarial Attacks on Neural Networks for Graph Data

读书笔记17：Adversarial Attacks on Neural Networks for Graph Data

Distillation as a Defense to Adversarial Perturbations against Deep Neural Networks

【PaperReading】OpenHGNN：An Open-Source Toolkit for Heterogeneous Graph Neural Networks

【翻译】Robust Graph Neural Networks 稳健的图神经网络

《Flag: Adversarial data augmentation for graph neural networks》阅读笔记【FLAG】

【PaperReading】Heterogeneous Graph Neural Network

(HGNN) Hypergraph Neural Networks

《CRFL:Certifiably Robust Federated Learning against Backdoor Attacks》

Session-based Recommendation with Graph Neural Networks ----2019AAAI

论文笔记：《GARNET: Reduced-Rank Topology Learning for Robust and Scalable Graph Neural Networks》

Graph Neural Networks

Equivariant Graph Neural Networks

Graph Neural Networks for Computer Vision

How Powerful are Graph Neural Networks?

Gated Graph Sequence Neural Networks

Domain Adaptation and Graph Neural Networks

A Robust Privacy-Preserving Federated Learning Model Against Model Poisoning Attacks

GeniePath：Graph Neural Networks with Adaptive Receptive Paths 论文详解 AAAI2019

Domain-Adversarial Neural Networks分析

Domain-Adversarial Training of Neural Networks

【增量/持续学习】2022 KDD Streaming Graph Neural Networks via Generative Replay

【KD】2022 ICLR Graph-Less Neural Networks: Teaching Old MLPs New Tricks Via Distillation

【KD】2022 KDD FreeKD: Free-direction Knowledge Distillation for Graph Neural Networks

论文那些事—DECISION-BASED ADVERSARIAL ATTACKS:RELIABLE ATTACKS AGAINST BLACK-BOX MACHINE LEARNING MODELS

DEFENSE-GAN: PROTECTING CLASSIFIERS AGAINST ADVERSARIAL ATTACKS USING GENERATIVE MODELS

GNN:Graph Neural Networks for Social Recommendation简介

IMAGE DENOISING WITH GRAPH-CONVOLUTIONAL NEURAL NETWORKS

EdgePool - Edge Contraction Pooling for Graph Neural Networks

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