Alternatives and similar repositories for GraphSNN:

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

• muhanzhang / NestedGNN
  ☆55Updated 3 years 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
• 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
• GraphPKU / JacobiConv
  How Powerful are Spectral Graph Neural Networks
  ☆70Updated last year
• Graph-COM / PEG
  ☆38Updated last year
• 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
• THUDM / GRAND-plus
  Code and dataset for paper "GRAND+: Scalable Graph Random Neural Networks"
  ☆32Updated 2 years ago
• ivam-he / BernNet
  PyTorch implementation of "BernNet: Learning Arbitrary Graph Spectral Filters via Bernstein Approximation"
  ☆52Updated last year
• RManLuo / GSNOP
  Official code implementation for WSDM 23 paper Graph Sequential Neural ODE Process for Link Prediction on Dynamic and Sparse Graphs.
  ☆33Updated last year
• nerdslab / bgrl
  PyTorch implementation of BGRL (https://arxiv.org/abs/2102.06514)
  ☆81Updated last year
• GemsLab / H2GCN
  Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)
  ☆101Updated 2 years ago
• EnyanDai / RSGNN
  An official PyTorch implementation of "Towards Robust Graph Neural Networks for Noisy Graphs with Sparse Labels" (WSDM 2022))
  ☆32Updated 2 years ago
• GemsLab / HeteRobust
  How does Heterophily Impact the Robustness of Graph Neural Networks? Theoretical Connections and Practical Implications (KDD'22)
  ☆12Updated 2 years ago
• BUPT-GAMMA / Graph-Structure-Estimation-Neural-Networks
  Source code for WWW 2021 paper "Graph Structure Estimation Neural Networks"
  ☆58Updated 3 years ago
• lsh0520 / RGCL
  Ratioanle-aware Graph Contrastive Learning codebase
  ☆40Updated last year
• GemsLab / CPGNN
  ☆28Updated 3 years ago
• junxia97 / SimGRACE
  [WWW 2022] "SimGRACE: A Simple Framework for Graph Contrastive Learning without Data Augmentation"
  ☆79Updated 2 years ago
• jianhao2016 / GPRGNN
  ☆131Updated last year
• susheels / adgcl
  Adversarial Graph Augmentation to Improve Graph Contrastive Learning
  ☆88Updated 3 years ago
• ChandlerBang / DeCorr
  [KDD 2022] Implementation of "Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective"
  ☆45Updated last year
• BorealisAI / SLAPS-GNN
  PyTorch code of "SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks"
  ☆87Updated 3 years ago
• TaiLvYuanLiang / HGWaveNet
  ☆12Updated 11 months ago
• snap-stanford / CAW
  ☆77Updated 2 years ago
• DM2-ND / CFLP
  Author: Tong Zhao (tzhao2@nd.edu). ICML 2022. Learning from Counterfactual Links for Link Prediction
  ☆66Updated 2 years ago
• Graph-COM / Neighborhood-Aware-Temporal-Network
  Yuhong Luo and Pan Li. Neighborhood-aware scalable temporal network representation learning. In Learning on Graphs, 2022.
  ☆28Updated last year
• ahxt / g-mixup
  [ICML2022] G-Mixup: Graph Data Augmentation for Graph Classification
  ☆97Updated 11 months ago
• zaixizhang / Graph_Transformer
  A pytorch implementation of graph transformer for node classification
  ☆29Updated last year
• Namkyeong / BGRL_Pytorch
  Pytorch implementation of "Large-Scale Representation Learning on Graphs via Bootstrapping"
  ☆78Updated 3 years ago
• flyingdoog / PTDNet
  Learning to Drop: Robust Graph Neural Network via Topological Denoising & Robust Graph Representation Learning via Neural Sparsification
  ☆77Updated 3 years ago
• RecklessRonan / GloGNN
  ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily
  ☆42Updated 2 years ago