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".
  ☆42Updated 4 years ago
• KangchengHou / gntk
  Implementation of Graph Neural Tangent Kernel (NeurIPS 2019)
  ☆103Updated 4 years ago
• tech-srl / bottleneck
  Code for the paper: "On the Bottleneck of Graph Neural Networks and Its Practical Implications"
  ☆94Updated 2 years ago
• devnkong / FLAG
  Official implementation of our FLAG paper (CVPR2022)
  ☆141Updated 2 years ago
• SwiftieH / IGNN
  Implicit Graph Neural Networks
  ☆60Updated 3 years ago
• stadlmax / Graph-Posterior-Network
  Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification (NeurIPS 2021)
  ☆41Updated 2 years ago
• leichen2018 / GNN-Substructure-Counting
  The official implementation of ''Can Graph Neural Networks Count Substructures?'' NeurIPS 2020
  ☆34Updated 3 years ago
• chentingpc / gfn
  Code for "Are Powerful Graph Neural Nets Necessary? A Dissection on Graph Classification"
  ☆51Updated 4 years ago
• vikasverma1077 / GraphMix
  Code for reproducing results in GraphMix paper
  ☆72Updated 2 years ago
• abojchevski / node_embedding_attack
  Adversarial Attacks on Node Embeddings via Graph Poisoning
  ☆59Updated 5 years ago
• HongtengXu / gwl
  Gromov-Wasserstein Learning for Graph Matching and Node Embedding
  ☆72Updated 5 years ago
• danielzuegner / robust-gcn-structure
  ☆12Updated 4 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).
  ☆28Updated last year
• HekpoMaH / algorithmic-concepts-reasoning
  ☆25Updated 3 years ago
• lukasjf / contrastive-gnn-explanation
  ☆19Updated 2 years ago
• AaltoPML / Rethinking-pooling-in-GNNs
  ☆62Updated 4 years ago
• Haggaim / InvariantGraphNetworks
  Code for the ICLR 2019 paper "Invariant and Equiovariant Graph Networks"
  ☆24Updated 4 years ago
• balcilar / gnn-spectral-expressive-power
  Code of "Analyzing the Expressive Power of Graph Neural Networks in a Spectral Perspective" paper published in ICLR2021
  ☆45Updated 3 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 2 years ago
• HongtengXu / s-gwl
  Scalable Gromov-Wasserstein Learning for Graph Partitioning and Matching
  ☆42Updated 5 years ago
• BorgwardtLab / WWL
  Wasserstein Weisfeiler-Lehman Graph Kernels
  ☆81Updated 4 months ago
• lxiaorui / ElasticGNN
  Official implementation of the ICML2021 paper "Elastic Graph Neural Networks"
  ☆40Updated 3 years ago
• navid-naderi / WEGL
  The implementation code for our paper Wasserstein Embedding for Graph Learning (ICLR 2021).
  ☆31Updated 3 years ago
• chrsmrrs / sparsewl
  Code for "Weisfeiler and Leman go sparse: Towards higher-order graph embeddings"
  ☆22Updated 2 years ago
• GentleZhu / Shift-Robust-GNNs
  "Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training Data" (NeurIPS 21')
  ☆47Updated 2 years ago
• PurdueMINDS / RelationalPooling
  ☆35Updated 5 years ago
• Kaixiong-Zhou / DGN
  Pytorch implementation of differentiable group normalization (NeurIPS 2020)
  ☆37Updated 4 years ago
• zxj32 / uncertainty-GNN
  Uncertainty Aware Semi-Supervised Learning on Graph Data
  ☆40Updated 3 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
• yang-han / P-reg
  Rethinking Graph Regularization for Graph Neural Networks (AAAI2021)
  ☆34Updated 3 years ago