Alternatives and similar repositories for A-Unifying-Framework-for-Spectrum-Preserving-Graph-Sparsification-and-Coarsening

Users that are interested in A-Unifying-Framework-for-Spectrum-Preserving-Graph-Sparsification-and-Coarsening are comparing it to the libraries listed below

• BorgwardtLab / WWL
  Wasserstein Weisfeiler-Lehman Graph Kernels
  ☆86Updated 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 4 years ago
• chrsmrrs / sparsewl
  Code for "Weisfeiler and Leman go sparse: Towards higher-order graph embeddings"
  ☆21Updated 4 years ago
• tech-srl / bottleneck
  Code for the paper: "On the Bottleneck of Graph Neural Networks and Its Practical Implications"
  ☆98Updated 3 years ago
• cvignac / SMP
  ☆30Updated 4 years ago
• leichen2018 / GNN-Substructure-Counting
  The official implementation of ''Can Graph Neural Networks Count Substructures?'' NeurIPS 2020
  ☆35Updated 4 years ago
• zekarias-tilahun / SelfGNN
  A PyTorch implementation of "SelfGNN: Self-supervised Graph Neural Networks without explicit negative sampling" paper, which appeared in …
  ☆30Updated 4 years ago
• tk-rusch / gradientgating
  Gradient gating (ICLR 2023)
  ☆55Updated 2 years ago
• mengliu1998 / DL4DisassortativeGraphs
  Papers about developing DL methods on disassortative graphs
  ☆48Updated 3 years ago
• RexYing / Rex-Ying-Thesis
  Rex Ying's Ph.D. Thesis, Stanford University
  ☆41Updated 3 years ago
• Saro00 / DGN
  Implementation of Directional Graph Networks in PyTorch and DGL
  ☆118Updated 4 years ago
• facebookresearch / shaDow_GNN
  [NeurIPS 2021]: Improve the GNN expressivity and scalability by decoupling the depth and receptive field of state-of-the-art GNN architec…
  ☆137Updated 3 years ago
• AaltoPML / Rethinking-pooling-in-GNNs
  ☆62Updated 5 years ago
• ebonilla / VGCN
  Variational Graph Convolutional Networks
  ☆23Updated 5 years ago
• muhanzhang / NestedGNN
  ☆57Updated 4 years ago
• SwiftieH / IGNN
  Implicit Graph Neural Networks
  ☆64Updated 4 years ago
• Kaixiong-Zhou / DGN
  Pytorch implementation of differentiable group normalization (NeurIPS 2020)
  ☆38Updated 5 years ago
• mims-harvard / G-Meta
  Graph meta learning via local subgraphs (NeurIPS 2020)
  ☆126Updated last year
• LingxiaoShawn / PairNorm
  Source code for PairNorm (ICLR 2020)
  ☆79Updated 5 years ago
• GentleZhu / Shift-Robust-GNNs
  "Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training Data" (NeurIPS 21')
  ☆49Updated 3 years ago
• twitter-research / sign
  SIGN: Scalable Inception Graph Network
  ☆95Updated 5 years ago
• rusty1s / pyg_autoscale
  Implementation of "GNNAutoScale: Scalable and Expressive Graph Neural Networks via Historical Embeddings" in PyTorch
  ☆166Updated 3 years ago
• BorgwardtLab / filtration_curves
  Code for the KDD 2021 paper 'Filtration Curves for Graph Representation'
  ☆18Updated 2 years ago
• Chen-Cai-OSU / GNN-Over-Smoothing
  A Note On Over-Smoothing for Graph Neural Network
  ☆20Updated 5 years ago
• chentingpc / gfn
  Code for "Are Powerful Graph Neural Nets Necessary? A Dissection on Graph Classification"
  ☆53Updated 5 years ago
• CheriseZhu / GIL
  The implementation of our NeurIPS 2020 paper "Graph Geometry Interaction Learning" (GIL)
  ☆46Updated 5 years ago
• FFTYYY / TWIRLS
  The code for the ICML 2021 paper "Graph Neural Networks Inspired by Classical Iterative Algorithms".
  ☆43Updated 4 years ago
• balcilar / gnn-matlang
  Code of "Breaking the Limits of Message Passing Graph Neural Networks" paper published in ICML2021
  ☆41Updated 4 years ago
• Shen-Lab / GDA-SpecReg
  [ICLR 2023] "Graph Domain Adaptation via Theory-Grounded Spectral Regularization" by Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen
  ☆23Updated 2 years ago
• toenshoff / CRaWl
  ☆26Updated last year