Alternatives and similar repositories for GFAttack:

Users that are interested in GFAttack are comparing it to the libraries listed below

• chisam0217 / Graph-Universal-Attack
  ☆18Updated 3 years ago
• abojchevski / node_embedding_attack
  Adversarial Attacks on Node Embeddings via Graph Poisoning
  ☆60Updated 5 years ago
• Hanjun-Dai / graph_adversarial_attack
  Adversarial Attack on Graph Structured Data (https://arxiv.org/abs/1806.02371)
  ☆129Updated 2 years ago
• KaidiXu / GCN_ADV_Train
  Adversarial training for Graph Neural Networks
  ☆60Updated 4 years ago
• danielzuegner / gnn-meta-attack
  Implementation of the paper "Adversarial Attacks on Graph Neural Networks via Meta Learning".
  ☆146Updated 3 years ago
• danielzuegner / nettack
  Implementation of the paper "Adversarial Attacks on Neural Networks for Graph Data".
  ☆220Updated 2 years ago
• TaoShuchang / G-NIA
  G-NIA model from "Single Node Injection Attack against Graph Neural Networks" (CIKM 2021)
  ☆28Updated 3 years ago
• THUDM / GIAAD
  Graph Injection Adversarial Attack & Defense Dataset , extracted from KDD CUP 2020 ML2 Track
  ☆21Updated 7 months ago
• RinneSz / CLGA
  Unsupervised Graph Poisoning Attack via Contrastive Loss Back-propagation, WWW22
  ☆17Updated 2 years ago
• ChandlerBang / pytorch-gnn-meta-attack
  Pytorch implementation of gnn meta attack (mettack). Paper title: Adversarial Attacks on Graph Neural Networks via Meta Learning.
  ☆21Updated 4 years ago
• danielzuegner / robust-gcn
  Implementation of the paper "Certifiable Robustness and Robust Training for Graph Convolutional Networks".
  ☆43Updated 4 years ago
• THUDM / tdgia
  code for paper TDGIA:Effective Injection Attacks on Graph Neural Networks (KDD 2021, research track)
  ☆19Updated 3 years ago
• graytowne / revisit_adv_rec
  A PyTorch implementation for the Recsys 2020 paper: Revisiting Adversarially Learned Injection Attacks Against Recommender Systems
  ☆23Updated 3 years ago
• xuanqing94 / AdvSSL
  A Unified Framework for Data Poisoning Attack to Graph-based Semi-supervised Learning
  ☆12Updated 5 years ago
• LFhase / GIA-HAO
  [ICLR 2022] Understanding and Improving Graph Injection Attack by Promoting Unnoticeability
  ☆37Updated last year
• huaxiuyao / HSML
  HSML for ICML 2019
  ☆51Updated 5 years ago
• rootlu / L2P-GNN
  Codes and datasets for AAAI-2021 paper "Learning to Pre-train Graph Neural Networks"
  ☆89Updated 4 years ago
• tangxianfeng / PA-GNN
  Implementation of paper "Transferring Robustness for Graph Neural Network Against Poisoning Attacks".
  ☆20Updated 5 years ago
• mori97 / JKNet-dgl
  A dgl implementation of Jumping Knowledge Networks (arXiv 1806.03536)
  ☆38Updated 6 years ago
• mims-harvard / GNNGuard
  Defending graph neural networks against adversarial attacks (NeurIPS 2020)
  ☆63Updated last year
• masakicktashiro / rgcn_pytorch_implementation
  ☆61Updated 4 years ago
• yifan-h / CS-GNN
  Measuring and Improving the Use of Graph Information in Graph Neural Networks
  ☆82Updated 8 months ago
• joeybose / Flexible-Fairness-Constraints
  Code for ICML2019 Paper "Compositional Invariance Constraints for Graph Embeddings"
  ☆50Updated 4 years ago
• EnyanDai / FairGNN
  A PyTorch implementation of "Say No to the Discrimination: Learning Fair Graph Neural Networks with Limited Sensitive Attribute Informati…
  ☆62Updated last year
• THUDM / grb
  Graph Robustness Benchmark: A scalable, unified, modular, and reproducible benchmark for evaluating the adversarial robustness of Graph M…
  ☆92Updated last year
• chentingpc / gfn
  Code for "Are Powerful Graph Neural Nets Necessary? A Dissection on Graph Classification"
  ☆51Updated 4 years ago
• fulifeng / GraphAT
  Graph Adversarial Training: Dynamically Regularizing Based on Graph Structure
  ☆22Updated 5 years ago
• fuying-wang / Data-poisoning-attacks-on-factorization-based-collaborative-filtering
  Data poisoning attack of recommend system using the algorithm of MF.
  ☆30Updated 6 years ago
• devnkong / FLAG
  Official implementation of our FLAG paper (CVPR2022)
  ☆143Updated 2 years ago
• ZW-ZHANG / RobustGCN
  This is a sample implementation of "Robust Graph Convolutional Networks Against Adversarial Attacks", KDD 2019.
  ☆11Updated 4 years ago