Alternatives and similar repositories for Graph-Universal-Attack:

Users that are interested in Graph-Universal-Attack are comparing it to the libraries listed below

• SwiftieH / GFAttack
  A Restricted Black-box Adversarial Framework Towards Attacking Graph Embedding Models
  ☆36Updated 3 years ago
• danielzuegner / gnn-meta-attack
  Implementation of the paper "Adversarial Attacks on Graph Neural Networks via Meta Learning".
  ☆146Updated 3 years ago
• Hanjun-Dai / graph_adversarial_attack
  Adversarial Attack on Graph Structured Data (https://arxiv.org/abs/1806.02371)
  ☆129Updated 2 years ago
• abojchevski / node_embedding_attack
  Adversarial Attacks on Node Embeddings via Graph Poisoning
  ☆60Updated 5 years ago
• KaidiXu / GCN_ADV_Train
  Adversarial training for Graph Neural Networks
  ☆60Updated 4 years ago
• danielzuegner / nettack
  Implementation of the paper "Adversarial Attacks on Neural Networks for Graph Data".
  ☆220Updated 2 years ago
• danielzuegner / robust-gcn
  Implementation of the paper "Certifiable Robustness and Robust Training for Graph Convolutional Networks".
  ☆43Updated 4 years ago
• xuanqing94 / AdvSSL
  A Unified Framework for Data Poisoning Attack to Graph-based Semi-supervised Learning
  ☆12Updated 5 years ago
• danielzuegner / robust-gcn-structure
  ☆12Updated 4 years ago
• malllabiisc / ConfGCN
  AISTATS 2019: Confidence-based Graph Convolutional Networks for Semi-Supervised Learning
  ☆59Updated 5 years ago
• liaopeiyuan / GAL
  [ICML 2021] Information Obfuscation of Graph Neural Networks
  ☆36Updated 3 years ago
• Shen-Lab / SS-GCNs
  [ICML 2020] "When Does Self-Supervision Help Graph Convolutional Networks?" by Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen
  ☆110Updated 3 years ago
• dawnranger / pytorch-AGNN
  Pytorch implementation of the Attention-based Graph Neural Network(AGNN)
  ☆146Updated 7 years ago
• chentingpc / gfn
  Code for "Are Powerful Graph Neural Nets Necessary? A Dissection on Graph Classification"
  ☆51Updated 4 years ago
• KelestZ / CondGen
  Conditional Structure Generation through Graph Variational Generative Adversarial Nets, NeurIPS 2019.
  ☆54Updated 5 years ago
• tangxianfeng / PA-GNN
  Implementation of paper "Transferring Robustness for Graph Neural Network Against Poisoning Attacks".
  ☆20Updated 5 years ago
• huangwb / AS-GCN
  tensorflow-as-gcn
  ☆92Updated 5 years ago
• masakicktashiro / rgcn_pytorch_implementation
  ☆61Updated 4 years ago
• devnkong / FLAG
  Official implementation of our FLAG paper (CVPR2022)
  ☆143Updated 2 years ago
• THUDM / GraphSGAN
  Implementation of "GraphSGAN", a GAN-based semi-supervised learning algorithm for graph data.
  ☆86Updated 5 years ago
• TaoShuchang / G-NIA
  G-NIA model from "Single Node Injection Attack against Graph Neural Networks" (CIKM 2021)
  ☆28Updated 3 years ago
• joeybose / Meta-Graph
  Meta-Learning for Few Shot Link Prediction
  ☆49Updated 4 years ago
• liqimai / Efficient-SSL
  Implementation for IGCN and GLP model in our paper "Label Efficient Semi-Supervised Learning via Graph Filtering."
  ☆75Updated 5 years ago
• zpeng27 / GMI
  Graph Representation Learning via Graphical Mutual Information Maximization
  ☆113Updated 4 years ago
• HKUST-KnowComp / semihin
  source code for the paper "Semi-supervised Learning over Heterogeneous Information Networks by Ensemble of Meta-graph Guided Random Walks…
  ☆31Updated 7 years ago
• jinyuan-jia / AttriGuard
  ☆23Updated 6 years ago
• bluer555 / KernelGCN
  Codes for NIPS 2019 Paper: Rethinking Kernel Methods for Node Representation Learning on Graphs
  ☆34Updated 5 years ago
• rootlu / L2P-GNN
  Codes and datasets for AAAI-2021 paper "Learning to Pre-train Graph Neural Networks"
  ☆89Updated 4 years ago
• yifan-h / CS-GNN
  Measuring and Improving the Use of Graph Information in Graph Neural Networks
  ☆82Updated 8 months ago
• Nate1874 / StructPool
  The code for our ICLR paper: StructPool: Structured Graph Pooling via Conditional Random Fields
  ☆58Updated 4 years ago