Alternatives and similar repositories for GraphCoarsening:

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

• zaixizhang / ANS-GT
  NeurIPS'22 Spotlight paper "Hierarchical Graph Transformer with Adaptive Node Sampling"
  ☆49Updated last year
• null-xyj / CoBFormer
  Implementation of ICML'24 Paper "Less is More: on the Over-Globalizing Problem in Graph Transformers"
  ☆39Updated 8 months ago
• Yujun-Yan / Heterophily_and_oversmoothing
  Codes for "Two Sides of the Same Coin: Heterophily and Oversmoothing in Graph Convolutional Neural Networks"
  ☆37Updated last year
• DSL-Lab / Specformer
  Transformer-based Spectral Graph Neural Networks
  ☆79Updated 3 months ago
• qwerfdsaplking / Graph-Trans
  A graph transformer framework
  ☆78Updated 2 years ago
• ivam-he / BernNet
  PyTorch implementation of "BernNet: Learning Arbitrary Graph Spectral Filters via Bernstein Approximation"
  ☆52Updated last year
• JHL-HUST / NAGphormer
  NAGphormer: A Tokenized Graph Transformer for Node Classification in Large Graphs
  ☆120Updated 10 months ago
• tk-rusch / gradientgating
  Gradient gating (ICLR 2023)
  ☆53Updated last year
• LUMIA-Group / OrderedGNN
  The official implementation of the paper "Ordered GNN: Ordering Message Passing to Deal with Heterophily and Over-smoothing" (ICLR 2023).
  ☆40Updated 10 months ago
• Graph-COM / ED-HNN
  [ICLR 2023] "Equivariant Hypergraph Diffusion Neural Operators" by Peihao Wang, Shenghao Yang, Yunyu Liu, Zhangyang Wang, Pan Li
  ☆41Updated 5 months ago
• ivam-he / ChebNetII
  PyTorch implementation of "Convolutional Neural Networks on Graphs with Chebyshev Approximation, Revisited"
  ☆33Updated last year
• ykiiiiii / ACMP
  ACMP: Allen-Cahn Message Passing with Attractive and Repulsive Forces for Graph Neural Networks(ICLR 2023)
  ☆18Updated last year
• LiuChuang0059 / graph-pooling-papers
  IJCAI‘23 Survey Track: Papers on Graph Pooling (GNN-Pooling)
  ☆113Updated last year
• SitaoLuan / ACM-GNN
  NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN fra…
  ☆76Updated 2 months ago
• luis-mueller / probing-graph-transformers
  Code for our paper "Attending to Graph Transformers"
  ☆84Updated last year
• jianhao2016 / AllSet
  This is the GitHub repository for our ICLR22 paper: "You are AllSet: A Multiset Function Framework for Hypergraph Neural Networks"
  ☆94Updated last year
• GemsLab / H2GCN
  Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)
  ☆101Updated 2 years ago
• LingxiaoShawn / GNNAsKernel
  Source code for From Stars to Subgraphs (ICLR 2022)
  ☆66Updated 10 months ago
• loukasa / graph-coarsening
  Multilevel graph coarsening algorithm with spectral and cut guarantees
  ☆87Updated 4 years ago
• Namkyeong / BGRL_Pytorch
  Pytorch implementation of "Large-Scale Representation Learning on Graphs via Bootstrapping"
  ☆78Updated 3 years ago
• RomanBresson / KAGNN
  This is the official repository for our paper KAGNNs: Kolmogorov-Arnold Networks meet Graph Learning.
  ☆38Updated last month
• muhanzhang / NestedGNN
  ☆55Updated 3 years ago
• asFeng / kergnns
  ☆30Updated 3 years ago
• FeiGSSS / Awesome-HigherOrderGraph
  Collection of papers relating data-driven higher-order graph/networks researches.
  ☆68Updated 2 years ago
• tufts-ml / graph-generation-EDGE
  EDGE: Efficient and Degree-Guided Graph Generation via Discrete Diffusion Modeling
  ☆54Updated 11 months ago
• jw9730 / ehnn
  [ECCV'22] Equivariant Hypergraph Neural Networks, in PyTorch
  ☆29Updated last year
• benfinkelshtein / CoGNN
  ☆49Updated 2 months ago
• cmavro / Graph-InfoClust-GIC
  [PAKDD 2021] Graph InfoClust: Leveraging cluster-level node information for unsupervised graph representation learning
  ☆33Updated 2 years ago
• BorealisAI / SLAPS-GNN
  PyTorch code of "SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks"
  ☆87Updated 3 years ago
• Graph-COM / PEG
  ☆38Updated last year