Alternatives and similar repositories for SEP:

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

• SitaoLuan / ACM-GNN
  NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN fra…
  ☆75Updated 4 months ago
• SongtaoLiu0823 / LAGNN
  [ICML 2022] Local Augmentation for Graph Neural Networks
  ☆66Updated 9 months ago
• ahxt / g-mixup
  [ICML2022] G-Mixup: Graph Data Augmentation for Graph Classification
  ☆101Updated last year
• junxia97 / SimGRACE
  [WWW 2022] "SimGRACE: A Simple Framework for Graph Contrastive Learning without Data Augmentation"
  ☆79Updated 2 years ago
• zepengzhang / awesome-graph-structure-learning
  A collection of papers on Graph Structural Learning (GSL)
  ☆54Updated last year
• BorealisAI / SLAPS-GNN
  PyTorch code of "SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks"
  ☆86Updated 3 years ago
• susheels / adgcl
  Adversarial Graph Augmentation to Improve Graph Contrastive Learning
  ☆88Updated 3 years ago
• PlusRoss / GRCN
  Graph revised convolutional network (ECML-PKDD 2020)
  ☆16Updated 4 years ago
• wokas36 / GraphSNN
  Graph Structured Neural Network
  ☆39Updated 2 years ago
• LUMIA-Group / OrderedGNN
  The official implementation of the paper "Ordered GNN: Ordering Message Passing to Deal with Heterophily and Over-smoothing" (ICLR 2023).
  ☆43Updated last year
• zaixizhang / Graph_Transformer
  A pytorch implementation of graph transformer for node classification
  ☆30Updated last year
• Yujun-Yan / Heterophily_and_oversmoothing
  Codes for "Two Sides of the Same Coin: Heterophily and Oversmoothing in Graph Convolutional Neural Networks"
  ☆37Updated 2 years ago
• GraphPKU / JacobiConv
  How Powerful are Spectral Graph Neural Networks
  ☆71Updated last year
• RingBDStack / VIB-GSL
  Code for "Graph Structure Learning with Variational Information Bottleneck" published in AAAI 2022
  ☆34Updated 2 years ago
• ivam-he / BernNet
  PyTorch implementation of "BernNet: Learning Arbitrary Graph Spectral Filters via Bernstein Approximation"
  ☆54Updated last year
• GemsLab / H2GCN
  Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)
  ☆101Updated 2 years ago
• zaixizhang / ProtGNN
  Official implementation of AAAI'22 paper "ProtGNN: Towards Self-Explaining Graph Neural Networks"
  ☆50Updated 2 years ago
• lsh0520 / RGCL
  Ratioanle-aware Graph Contrastive Learning codebase
  ☆40Updated last year
• THUDM / GRAND-plus
  Code and dataset for paper "GRAND+: Scalable Graph Random Neural Networks"
  ☆33Updated 3 years ago
• RecklessRonan / GloGNN
  ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily
  ☆43Updated 2 years ago
• mengliu1998 / DL4DisassortativeGraphs
  Papers about developing DL methods on disassortative graphs
  ☆48Updated 2 years ago
• zaixizhang / ANS-GT
  NeurIPS'22 Spotlight paper "Hierarchical Graph Transformer with Adaptive Node Sampling"
  ☆50Updated last year
• Graph-COM / PEG
  ☆38Updated last year
• LiuChuang0059 / graph-pooling-papers
  IJCAI‘23 Survey Track: Papers on Graph Pooling (GNN-Pooling)
  ☆113Updated 2 years ago
• yuwvandy / DPGNN
  ☆39Updated last year
• GemsLab / CPGNN
  ☆29Updated 3 years ago
• hengruizhang98 / CCA-SSG
  Codes for 'From Canonical Correlation Analysis to Self-supervised Graph Neural Networks'. https://arxiv.org/abs/2106.12484
  ☆68Updated last year
• Amanda-Zheng / SFGC
  Pytorch implementation of NeurIPS-23:"Structure-free Graph Condensation (SFGC): From Large-scale Graphs to Condensed Graph-free Data"
  ☆30Updated last year
• qitianwu / GraphOOD-EERM
  The official implementation for ICLR22 paper "Handling Distribution Shifts on Graphs: An Invariance Perspective"
  ☆86Updated 2 years ago
• wondergo2017 / DIDA
  Implementation Codes for NeurIPS22 paper "Dynamic Graph Neural Networks Under Spatio-Temporal Distribution Shift"
  ☆20Updated 2 years ago