Alternatives and similar repositories for sparse_smoothing:

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

• danielzuegner / robust-gcn
  Implementation of the paper "Certifiable Robustness and Robust Training for Graph Convolutional Networks".
  ☆43Updated 4 years ago
• abojchevski / node_embedding_attack
  Adversarial Attacks on Node Embeddings via Graph Poisoning
  ☆60Updated 5 years ago
• stadlmax / Graph-Posterior-Network
  Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification (NeurIPS 2021)
  ☆42Updated 2 years ago
• tech-srl / bottleneck
  Code for the paper: "On the Bottleneck of Graph Neural Networks and Its Practical Implications"
  ☆94Updated 2 years ago
• KangchengHou / gntk
  Implementation of Graph Neural Tangent Kernel (NeurIPS 2019)
  ☆103Updated 5 years ago
• SwiftieH / IGNN
  Implicit Graph Neural Networks
  ☆60Updated 3 years 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
• devnkong / FLAG
  Official implementation of our FLAG paper (CVPR2022)
  ☆143Updated 2 years ago
• chrsmrrs / sparsewl
  Code for "Weisfeiler and Leman go sparse: Towards higher-order graph embeddings"
  ☆22Updated 3 years ago
• lxiaorui / ElasticGNN
  Official implementation of the ICML2021 paper "Elastic Graph Neural Networks"
  ☆41Updated 3 years ago
• danielzuegner / robust-gcn-structure
  ☆12Updated 4 years ago
• tangxianfeng / PA-GNN
  Implementation of paper "Transferring Robustness for Graph Neural Network Against Poisoning Attacks".
  ☆20Updated 5 years ago
• BorgwardtLab / WWL
  Wasserstein Weisfeiler-Lehman Graph Kernels
  ☆81Updated 6 months ago
• AaltoPML / Rethinking-pooling-in-GNNs
  ☆62Updated 4 years ago
• chentingpc / gfn
  Code for "Are Powerful Graph Neural Nets Necessary? A Dissection on Graph Classification"
  ☆51Updated 4 years ago
• twitter-research / sign
  SIGN: Scalable Inception Graph Network
  ☆96Updated 4 years ago
• lukasjf / contrastive-gnn-explanation
  ☆19Updated 2 years ago
• sigeisler / reliable_gnn_via_robust_aggregation
  This repository contains the official implementation of the paper "Reliable Graph Neural Networks via Robust Aggregation" (NeurIPS, 2020)…
  ☆17Updated 3 years ago
• PurdueMINDS / Equivalence
  Equivalence Between Structural Representations and Positional Node Embeddings
  ☆21Updated 5 years ago
• leichen2018 / GNN-Substructure-Counting
  The official implementation of ''Can Graph Neural Networks Count Substructures?'' NeurIPS 2020
  ☆34Updated 4 years ago
• joisino / random-features
  Code for "Random Features Strengthen Graph Neural Networks" (SDM 2021)
  ☆22Updated 4 years ago
• ebonilla / VGCN
  Variational Graph Convolutional Networks
  ☆22Updated 4 years ago
• abojchevski / graph_cert
  Certifiable Robustness to Graph Perturbations
  ☆13Updated 4 years ago
• KaidiXu / GCN_ADV_Train
  Adversarial training for Graph Neural Networks
  ☆60Updated 4 years ago
• LFhase / GIA-HAO
  [ICLR 2022] Understanding and Improving Graph Injection Attack by Promoting Unnoticeability
  ☆37Updated last year
• vikasverma1077 / GraphMix
  Code for reproducing results in GraphMix paper
  ☆72Updated 2 years ago
• mims-harvard / GNNGuard
  Defending graph neural networks against adversarial attacks (NeurIPS 2020)
  ☆63Updated last year
• claying / GCKN
  Pytorch Implementation of Graph Convolutional Kernel Networks
  ☆54Updated 2 years ago
• KarolisMart / DropGNN
  The official implementation of DropGNN: Random Dropouts Increase the Expressiveness of Graph Neural Networks (NeurIPS 2021)
  ☆25Updated 2 years ago
• navid-naderi / WEGL
  The implementation code for our paper Wasserstein Embedding for Graph Learning (ICLR 2021).
  ☆34Updated 4 years ago