Alternatives and similar repositories for tdgia

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

• TaoShuchang / G-NIA
  G-NIA model from "Single Node Injection Attack against Graph Neural Networks" (CIKM 2021)
  ☆30Updated 3 years ago
• THUDM / GIAAD
  Graph Injection Adversarial Attack & Defense Dataset , extracted from KDD CUP 2020 ML2 Track
  ☆22Updated 9 months ago
• BUPT-GAMMA / RoHe
  ☆20Updated 3 years ago
• likuanppd / STABLE
  source code of KDD 2022 paper "Reliable Representations Make A Stronger Defender: Unsupervised Structure Refinement for Robust GNN".
  ☆28Updated last year
• LFhase / GIA-HAO
  [ICLR 2022] Understanding and Improving Graph Injection Attack by Promoting Unnoticeability
  ☆38Updated last year
• THUDM / grb
  Graph Robustness Benchmark: A scalable, unified, modular, and reproducible benchmark for evaluating the adversarial robustness of Graph M…
  ☆95Updated last year
• KaidiXu / GCN_ADV_Train
  Adversarial training for Graph Neural Networks
  ☆60Updated 4 years ago
• EnyanDai / RSGNN
  An official PyTorch implementation of "Towards Robust Graph Neural Networks for Noisy Graphs with Sparse Labels" (WSDM 2022))
  ☆33Updated 2 years ago
• EdisonLeeeee / GreatX
  A graph reliability toolbox based on PyTorch and PyTorch Geometric (PyG).
  ☆85Updated 7 months ago
• alexfanjn / GANI
  The relevant codes for "GANI: Global Attacks on Graph Neural Networks via Imperceptible Node Injections".
  ☆14Updated last year
• jumxglhf / G2A2C
  Official repository for AAAI'23 paper: Let Graph be the Go Board: Gradient-free Node Injection Attack for Graph Neural Networks via Reinf…
  ☆25Updated 2 years ago
• zaixizhang / graphbackdoor
  A PyTorch implementation of "Backdoor Attacks to Graph Neural Networks" (SACMAT'21)
  ☆39Updated 3 years ago
• liun-online / SpCo
  The source code of SpCo
  ☆34Updated 2 years ago
• mims-harvard / GNNGuard
  Defending graph neural networks against adversarial attacks (NeurIPS 2020)
  ☆64Updated last year
• yushundong / EDITS
  Open source code for paper "EDITS: Modeling and Mitigating Data Bias for Graph Neural Networks".
  ☆27Updated 2 years ago
• LoadingByte / are-gnn-defenses-robust
  Adaptive evaluation reveals that most examined adversarial defenses for GNNs show no or only marginal improvement in robustness. (NeurIPS…
  ☆29Updated 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
• ispamm / FairDrop
  ☆14Updated 3 years ago
• EnyanDai / FairGNN
  A PyTorch implementation of "Say No to the Discrimination: Learning Fair Graph Neural Networks with Limited Sensitive Attribute Informati…
  ☆65Updated last year
• thupchnsky / sgc_unlearn
  Certified (approximate) machine unlearning for simplified graph convolutional networks (SGCs) with theoretical guarantees (ICLR 2023)
  ☆19Updated 2 years ago
• RinneSz / CLGA
  Unsupervised Graph Poisoning Attack via Contrastive Loss Back-propagation, WWW22
  ☆17Updated 2 years ago
• yuwvandy / FairVGNN
  ☆26Updated 2 years ago
• EdisonLeeeee / Awesome-Fair-Graph-Learning
  Paper List for Fair Graph Learning (FairGL).
  ☆138Updated 8 months ago
• sigeisler / robustness_of_gnns_at_scale
  This repository contains the official implementation of the paper "Robustness of Graph Neural Networks at Scale" (NeurIPS, 2021).
  ☆30Updated last year
• jma712 / GEAR
  ☆18Updated 3 years ago
• susheels / adgcl
  Adversarial Graph Augmentation to Improve Graph Contrastive Learning
  ☆88Updated 3 years ago
• isail-laboratory / iDEA-iSAIL-Reading-Group
  ☆26Updated last month
• wyl7 / DCI-pytorch
  The pytorch implementation of DCI (SIGIR2021).
  ☆34Updated 2 years ago
• saper0 / adversarial_training
  Codebase used to generate the results for NeurIPS23 "Adversarial Training for Graph Neural Networks: Pitfalls, Solutions, and New Directi…
  ☆11Updated last year
• chirag-agarwall / nifty
  Code for paper https://arxiv.org/abs/2102.13186
  ☆44Updated 4 years ago