Alternatives and similar repositories for GNN-Over-Smoothing

Users that are interested in GNN-Over-Smoothing are comparing it to the libraries listed below

• 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
• muhanzhang / NestedGNN
  ☆57Updated 3 years ago
• susheels / gnns-and-local-assortativity
  This repo contains a reference implementation for the paper "Breaking the Limit of Graph Neural Networks by Improving the Assortativity o…
  ☆32Updated 3 years ago
• tk-rusch / gradientgating
  Gradient gating (ICLR 2023)
  ☆53Updated 2 years ago
• FFTYYY / TWIRLS
  The code for the ICML 2021 paper "Graph Neural Networks Inspired by Classical Iterative Algorithms".
  ☆43Updated 4 years ago
• qslim / gnn-spectrum
  Implementation of the paper "A New Perspective on the Effects of Spectrum in Graph Neural Networks"
  ☆17Updated 3 years ago
• mengliu1998 / DL4DisassortativeGraphs
  Papers about developing DL methods on disassortative graphs
  ☆48Updated 3 years ago
• lxiaorui / ElasticGNN
  Official implementation of the ICML2021 paper "Elastic Graph Neural Networks"
  ☆42Updated 4 years ago
• GemsLab / CPGNN
  ☆29Updated 3 years ago
• GemsLab / H2GCN
  Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)
  ☆104Updated 2 months ago
• balcilar / gnn-matlang
  Code of "Breaking the Limits of Message Passing Graph Neural Networks" paper published in ICML2021
  ☆41Updated 4 years ago
• lxiaorui / AirGNN
  ☆21Updated 2 years ago
• Yujun-Yan / Heterophily_and_oversmoothing
  Codes for "Two Sides of the Same Coin: Heterophily and Oversmoothing in Graph Convolutional Neural Networks"
  ☆38Updated 2 years ago
• wokas36 / GraphSNN
  Graph Structured Neural Network
  ☆40Updated 3 years ago
• 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
• jctops / understanding-oversquashing
  ☆41Updated 3 years ago
• snap-research / non-contrastive-link-prediction
  [ICLR 2023] Link Prediction with Non-Contrastive Learning
  ☆26Updated 2 years ago
• Kaixiong-Zhou / EGNN
  Energetic GraphNeural Networks (EGNN) implementation based on Dirichlet Energy Constrained Learning.
  ☆27Updated 3 years ago
• chrsmrrs / sparsewl
  Code for "Weisfeiler and Leman go sparse: Towards higher-order graph embeddings"
  ☆22Updated 3 years ago
• cvignac / SMP
  ☆28Updated 3 years ago
• ChandlerBang / DeCorr
  [KDD 2022] Implementation of "Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective"
  ☆45Updated last year
• RPaolino / fLode
  ☆18Updated last year
• ykiiiiii / ACMP
  ACMP: Allen-Cahn Message Passing with Attractive and Repulsive Forces for Graph Neural Networks(ICLR 2023)
  ☆20Updated last year
• yifeiwang77 / DGC
  Official Code of Decoupled Graph Convolution (DGC)
  ☆16Updated 3 years ago
• LingxiaoShawn / GNNAsKernel
  Source code for From Stars to Subgraphs (ICLR 2022)
  ☆69Updated last year
• Namkyeong / BGRL_Pytorch
  Pytorch implementation of "Large-Scale Representation Learning on Graphs via Bootstrapping"
  ☆81Updated 3 years ago
• harryjo97 / EHGNN
  Official Code Repository for the paper "Edge Representation Learning with Hypergraphs" (NeurIPS 2021)
  ☆53Updated 2 years ago
• hedongxiao-tju / BM-GCN
  The code of paper "Block Modeling-Guided Graph Convolutional Neural Networks".
  ☆33Updated 3 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
• flyingtango / DiGCL
  The PyTorch implementation of Directed Graph Contrastive Learning (DiGCL), NeurIPS-2021
  ☆36Updated 3 years ago