Alternatives and similar repositories for DeepRobust

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

• safe-graph / graph-adversarial-learning-literature
  A curated list of adversarial attacks and defenses papers on graph-structured data.
  ☆861Updated last year
• EdisonLeeeee / Graph-Adversarial-Learning
  A curated collection of adversarial attack and defense on graph data.
  ☆575Updated 2 years ago
• ChandlerBang / awesome-graph-attack-papers
  Adversarial attacks and defenses on Graph Neural Networks.
  ☆389Updated last year
• danielzuegner / nettack
  Implementation of the paper "Adversarial Attacks on Neural Networks for Graph Data".
  ☆221Updated 3 years ago
• danielzuegner / gnn-meta-attack
  Implementation of the paper "Adversarial Attacks on Graph Neural Networks via Meta Learning".
  ☆154Updated 4 years ago
• KaidiXu / GCN_ADV_Train
  Adversarial training for Graph Neural Networks
  ☆61Updated 4 years ago
• P2333 / Papers-of-Robust-ML
  Related papers for robust machine learning
  ☆567Updated 2 years ago
• zaixizhang / graphbackdoor
  A PyTorch implementation of "Backdoor Attacks to Graph Neural Networks" (SACMAT'21)
  ☆44Updated 4 years ago
• ChandlerBang / Pro-GNN
  Implementation of the KDD 2020 paper "Graph Structure Learning for Robust Graph Neural Networks"
  ☆301Updated 2 years ago
• xingchenwan / grabnel
  [NeurIPS '21] Adversarial Attacks on Graph Classification via Bayesian Optimisation (GRABNEL)
  ☆14Updated 4 years ago
• THUDM / grb
  Graph Robustness Benchmark: A scalable, unified, modular, and reproducible benchmark for evaluating the adversarial robustness of Graph M…
  ☆97Updated 2 years ago
• Hanjun-Dai / graph_adversarial_attack
  Adversarial Attack on Graph Structured Data (https://arxiv.org/abs/1806.02371)
  ☆130Updated 3 years ago
• zhaohan-xi / GraphBackdoor
  ☆58Updated 3 years ago
• THUDM / tdgia
  code for paper TDGIA:Effective Injection Attacks on Graph Neural Networks (KDD 2021, research track)
  ☆22Updated 4 years ago
• ventr1c / UGBA
  An official PyTorch implementation of "Unnoticeable Backdoor Attacks on Graph Neural Networks" (WWW 2023)
  ☆61Updated 2 years ago
• mims-harvard / GNNGuard
  Defending graph neural networks against adversarial attacks (NeurIPS 2020)
  ☆71Updated 2 years ago
• EdisonLeeeee / GraphGallery
  GraphGallery is a gallery for benchmarking Graph Neural Networks
  ☆472Updated 2 years ago
• thu-ml / ares
  A Python library for adversarial machine learning focusing on benchmarking adversarial robustness.
  ☆519Updated 2 years ago
• xujing1994 / Explanability_bkd_gnn
  Implementation of paper "Explanability-based backdoor attacks against graph neural networks"
  ☆12Updated 3 years ago
• SXKDZ / awesome-self-supervised-learning-for-graphs
  A curated list for awesome self-supervised learning for graphs.
  ☆388Updated 3 years ago
• xkLi-Allen / Awesome-GNN-Research
  My future research
  ☆416Updated 2 years ago
• DropEdge / DropEdge
  This is a Pytorch implementation of paper: DropEdge: Towards Deep Graph Convolutional Networks on Node Classification
  ☆475Updated 3 years ago
• Mark12Ding / GNN-Practical-Attack
  Code for Towards More Practical Adversarial Attacks on Graph Neural Networks (NeurIPS 2020)
  ☆28Updated 4 years ago
• FedML-AI / FedGraphNN
  FedGraphNN: A Federated Learning Platform for Graph Neural Networks with MLOps Support. The previous research version is accepted to ICLR…
  ☆183Updated last year
• EdisonLeeeee / RS-Adversarial-Learning
  A curated collection of adversarial attack and defense on recommender systems.
  ☆136Updated 3 years ago
• diningphil / gnn-comparison
  Official Repository of "A Fair Comparison of Graph Neural Networks for Graph Classification", ICLR 2020
  ☆398Updated last year
• RexYing / gnn-model-explainer
  gnn explainer
  ☆1,017Updated last year
• shchur / gnn-benchmark
  Framework for evaluating Graph Neural Network models on semi-supervised node classification task
  ☆487Updated 7 years ago
• tao-bai / attack-and-defense-methods
  A curated list of papers on adversarial machine learning (adversarial examples and defense methods).
  ☆212Updated 3 years ago
• Shen-Lab / GraphCL
  [NeurIPS 2020] "Graph Contrastive Learning with Augmentations" by Yuning You, Tianlong Chen, Yongduo Sui, Ting Chen, Zhangyang Wang, Yang…
  ☆618Updated last year