Alternatives and similar repositories for AdvSSL:

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

• danielzuegner / robust-gcn
  Implementation of the paper "Certifiable Robustness and Robust Training for Graph Convolutional Networks".
  ☆42Updated 4 years ago
• abojchevski / node_embedding_attack
  Adversarial Attacks on Node Embeddings via Graph Poisoning
  ☆59Updated 5 years ago
• nikhil-dce / SBM-meet-GNN
  Implementation of SBM-meet-GNN
  ☆22Updated 5 years ago
• vwz / AGE
  Active Learning for Graph Embedding
  ☆32Updated 7 years ago
• bluer555 / KernelGCN
  Codes for NIPS 2019 Paper: Rethinking Kernel Methods for Node Representation Learning on Graphs
  ☆34Updated 4 years ago
• tangxianfeng / PA-GNN
  Implementation of paper "Transferring Robustness for Graph Neural Network Against Poisoning Attacks".
  ☆20Updated 4 years ago
• fulifeng / GraphAT
  Graph Adversarial Training: Dynamically Regularizing Based on Graph Structure
  ☆22Updated 4 years ago
• Kaixiong-Zhou / DGN
  Pytorch implementation of differentiable group normalization (NeurIPS 2020)
  ☆37Updated 4 years ago
• InkToYou / WL-Kernel-DGL
  An Implementation of 1-Weisfeiler-Lehman Algorithm using Deep Graph Library
  ☆9Updated 4 years ago
• DEEP-PolyU / GraphRNA_KDD19
  Graph Recurrent Networks with Attributed Random Walks
  ☆28Updated last year
• daiquanyu / AdvT4NE_WWW2019
  Adversarial Training Methods for Network Embedding, WWW2019.
  ☆27Updated 5 years ago
• SwiftieH / GFAttack
  A Restricted Black-box Adversarial Framework Towards Attacking Graph Embedding Models
  ☆36Updated 3 years ago
• Davidham3 / deeper_insights_into_GCNs
  Deeper insights into graph convolutional networks for semi-supervised learning
  ☆19Updated 6 years ago
• matenure / OTCoarsening
  Unsupervised Learning of Graph Hierarchical Abstractions with Differentiable Coarsening and Optimal Transport
  ☆36Updated 3 years ago
• ebonilla / VGCN
  Variational Graph Convolutional Networks
  ☆22Updated 4 years ago
• abojchevski / paican
  Implementation of "Bayesian Robust Attributed Graph Clustering: Joint Learning of Partial Anomalies and Group Structure".
  ☆24Updated 4 years ago
• yangji9181 / AutoPath
  The AutoPath pipeline for similarity modeling on heterogeneous networks with automatic path discovery
  ☆11Updated 5 years ago
• lxiaorui / ElasticGNN
  Official implementation of the ICML2021 paper "Elastic Graph Neural Networks"
  ☆40Updated 3 years ago
• shuaiOKshuai / D2AGE
  The source codes for D2AGE model. Distance-aware DAG Embedding for Proximity Search on Heterogeneous Graphs.
  ☆12Updated 6 years ago
• chentingpc / gfn
  Code for "Are Powerful Graph Neural Nets Necessary? A Dissection on Graph Classification"
  ☆51Updated 4 years ago
• TaoShuchang / G-NIA
  G-NIA model from "Single Node Injection Attack against Graph Neural Networks" (CIKM 2021)
  ☆27Updated 3 years ago
• abojchevski / graph_cert
  Certifiable Robustness to Graph Perturbations
  ☆13Updated 4 years ago
• lxiaorui / AirGNN
  ☆19Updated 2 years ago
• liqimai / gcn
  Implementation of Graph Convolutional Networks in TensorFlow
  ☆45Updated 6 years ago
• aravindsankar28 / Meta-GNN
  Implementation of Meta-GNN in TensorFlow
  ☆47Updated 3 years ago
• joeybose / Flexible-Fairness-Constraints
  Code for ICML2019 Paper "Compositional Invariance Constraints for Graph Embeddings"
  ☆50Updated 4 years ago
• ninghaohello / Interpretation2Adversary
  Adversarial learning by utilizing model interpretation
  ☆10Updated 6 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 3 years ago
• liaopeiyuan / GAL
  [ICML 2021] Information Obfuscation of Graph Neural Networks
  ☆36Updated 3 years ago