Alternatives and similar repositories for Simplifying-Clustering-with-Graph-Neural-Networks:

Users that are interested in Simplifying-Clustering-with-Graph-Neural-Networks are comparing it to the libraries listed below

• pbielak / graph-barlow-twins
  The official implementation of the Graph Barlow Twins method with the experimental pipeline
  ☆30Updated last year
• xiongbo010 / QGCN
  PyTorch implementation of Pseudo-Riemannian Graph Convolutional Networks (NeurIPS'22))
  ☆16Updated 9 months ago
• snap-stanford / conformalized-gnn
  Uncertainty Quantification over Graph with Conformalized Graph Neural Networks (NeurIPS 2023)
  ☆77Updated last year
• wanyu-lin / ICML2021-Gem
  Official code for the ICML 2021 paper "Generative Causal Explanations for Graph Neural Networks."
  ☆66Updated 3 years ago
• zaixizhang / ProtGNN
  Official implementation of AAAI'22 paper "ProtGNN: Towards Self-Explaining Graph Neural Networks"
  ☆51Updated 2 years ago
• BorealisAI / SLAPS-GNN
  PyTorch code of "SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks"
  ☆86Updated 3 years ago
• vunhatminh / PGMExplainer
  Generating PGM Explanation for GNN predictions
  ☆74Updated last year
• stadlmax / Graph-Posterior-Network
  Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification (NeurIPS 2021)
  ☆42Updated 2 years ago
• a-lucic / cf-gnnexplainer
  ☆57Updated 2 years ago
• GraphFramEx / graphframex
  GraphFramEx: a systematic evaluation framework for explainability methods on GNNs
  ☆44Updated last year
• balcilar / gnn-spectral-expressive-power
  Code of "Analyzing the Expressive Power of Graph Neural Networks in a Spectral Perspective" paper published in ICLR2021
  ☆46Updated 3 years ago
• OneForward / UniGNN
  Source code for the paper UniGNN: a Unified Framework for Graph and Hypergraph Neural Networks (IJCAI 2021).
  ☆66Updated 3 years ago
• RexYing / Rex-Ying-Thesis
  Rex Ying's Ph.D. Thesis, Stanford University
  ☆42Updated 2 years ago
• ChandlerBang / AutoSSL
  [ICLR 2022] Implementation of paper "Automated Self-Supervised Learning for Graphs"
  ☆41Updated 2 years ago
• yuwvandy / DPGNN
  ☆39Updated last year
• GentleZhu / Shift-Robust-GNNs
  "Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training Data" (NeurIPS 21')
  ☆47Updated 2 years ago
• Graph-COM / ED-HNN
  [ICLR 2023] "Equivariant Hypergraph Diffusion Neural Operators" by Peihao Wang, Shenghao Yang, Yunyu Liu, Zhangyang Wang, Pan Li
  ☆45Updated 7 months ago
• RPaolino / fLode
  ☆18Updated last year
• mtang724 / NWR-GAE
  ☆38Updated 2 years ago
• lcosmo / DGM_pytorch
  ☆53Updated 2 years ago
• ChandlerBang / GTrans
  [ICLR'23] Implementation of "Empowering Graph Representation Learning with Test-Time Graph Transformation"
  ☆56Updated last year
• zekarias-tilahun / SelfGNN
  A PyTorch implementation of "SelfGNN: Self-supervised Graph Neural Networks without explicit negative sampling" paper, which appeared in …
  ☆30Updated 3 years ago
• tk-rusch / gradientgating
  Gradient gating (ICLR 2023)
  ☆53Updated last year
• AntonioLonga / Explaining-the-Explainers-in-Graph-Neural-Networks
  Repository associated to the paper: "Explaining the Explainers in Graph Neural Networks: a Comparative Study"
  ☆35Updated last year
• snap-research / MLPInit-for-GNNs
  [ICLR 2023] MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP Initialization
  ☆77Updated 2 years ago
• nerdslab / bgrl
  PyTorch implementation of BGRL (https://arxiv.org/abs/2102.06514)
  ☆81Updated last year
• BorgwardtLab / filtration_curves
  Code for the KDD 2021 paper 'Filtration Curves for Graph Representation'
  ☆18Updated last year
• AaltoPML / Rethinking-pooling-in-GNNs
  ☆62Updated 4 years ago
• Graph-COM / GraphMaker
  [TMLR] GraphMaker: Can Diffusion Models Generate Large Attributed Graphs?
  ☆55Updated last week
• xiangwang1223 / reinforced_causal_explainer
  Reinforced Causal Explainer for Graph Neural Networks, TPAMI2022
  ☆35Updated 2 years ago