【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

目录

3.1 结点特征映射

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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》

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

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Domain-Adversarial Training of Neural Networks

【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

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

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

《Few-Shot Learning with Graph Neural Networks》

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