Alternatives and similar repositories for LGI-GT

Users that are interested in LGI-GT are comparing it to the libraries listed below

• weitianxin / HyperGCL
  [NeurIPS 2022] "Augmentations in Hypergraph Contrastive Learning: Fabricated and Generative" by Tianxin Wei, Yuning You, Tianlong Chen, Y…
  ☆61Updated 3 years ago
• sheldonresearch / HWNN
  Xiangguo Sun et al. Heterogeneous Hypergraph Embedding for Graph Classification, WSDM2021
  ☆31Updated 5 months ago
• hengruizhang98 / CCA-SSG
  Codes for 'From Canonical Correlation Analysis to Self-supervised Graph Neural Networks'. https://arxiv.org/abs/2106.12484
  ☆70Updated 2 years ago
• VITA-Group / Graph-Mixture-of-Experts
  [NeurIPS'23] Graph Mixture of Experts: Learning on Large-Scale Graphs with Explicit Diversity Modeling. Haotao Wang, Ziyu Jiang, Yuning Y…
  ☆57Updated 2 years ago
• Graph-COM / ED-HNN
  [ICLR 2023] "Equivariant Hypergraph Diffusion Neural Operators" by Peihao Wang, Shenghao Yang, Yunyu Liu, Zhangyang Wang, Pan Li
  ☆49Updated last year
• mpanpan / SimGRACE
  [WWW 2022] "A Simple Framework for Graph Contrastive Learning without Data Augmentation"
  ☆18Updated 3 years ago
• hedongxiao-tju / BM-GCN
  The code of paper "Block Modeling-Guided Graph Convolutional Neural Networks".
  ☆33Updated 3 years ago
• lsh0520 / RGCL
  Ratioanle-aware Graph Contrastive Learning codebase
  ☆44Updated 2 years ago
• ha-lins / PGCL
  The code of “Prototypical Graph Contrastive Learning”. [TNNLS 2022]
  ☆24Updated 3 years ago
• BUPT-GAMMA / Uncovering-the-Structural-Fairness-in-Graph-Contrastive-Learning
  Source code for NeurIPS 2022 paper "Uncovering the Structural Fairness in Graph Contrastive Learning"
  ☆29Updated 3 years ago
• EdisonLeeeee / MaskGAE
  [KDD 2023] What’s Behind the Mask: Understanding Masked Graph Modeling for Graph Autoencoders
  ☆91Updated last year
• ChandlerBang / DeCorr
  [KDD 2022] Implementation of "Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective"
  ☆45Updated last year
• limengran98 / HGTN
  The codes of Hpyergraph Transformer Nerual Networks.
  ☆21Updated last year
• TrustAGI-Lab / MERIT
  [IJCAI 2021] A PyTorch implementation of "Multi-Scale Contrastive Siamese Networks for Self-Supervised Graph Representation Learning".
  ☆40Updated 3 years ago
• NeXAIS / DDM
  Directional diffusion models
  ☆43Updated last year
• shenxiaocam / NCLA
  Neighbor Contrastive Learning on Learnable Graph Augmentation
  ☆37Updated last year
• yifeiacc / COSTA
  Code for KDD'22 paper, COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive Learning
  ☆49Updated 2 years ago
• zjunet / GPF
  The code Implementation of the paper “Universal Prompt Tuning for Graph Neural Networks”.
  ☆35Updated 2 years ago
• cszhangzhen / MVPool
  Hierarchical Multi-View Graph Pooling with Structure Learning (TKDE-2021)
  ☆25Updated 3 years ago
• zjunet / DropMessage
  The implementation for DropMessage.
  ☆38Updated 2 years ago
• BorgwardtLab / SAT
  Official Pytorch code for Structure-Aware Transformer.
  ☆262Updated 2 years ago
• Somedaywilldo / AutoGCL
  AutoGCL: Automated Graph Contrastive Learning via Learnable View Generators (AAAI 2022)
  ☆48Updated 3 years ago
• wenzhilics / GraphSHA
  "GraphSHA: Synthesizing Harder Samples for Class-Imbalanced Node Classification" in KDD'23
  ☆31Updated last year
• tengxiao1 / GraphACL
  GraphACL: Simple and Asymmetric Graph Contrastive Learning (NeurIPS 2023)
  ☆34Updated last year
• Ffffffffire / HINormer
  ☆34Updated 2 years ago
• null-xyj / CoBFormer
  Implementation of ICML'24 Paper "Less is More: on the Over-Globalizing Problem in Graph Transformers"
  ☆46Updated last year
• BUPT-GAMMA / GCIL
  Code for AAAI-2024 paper: Graph Contrastive Invariant Learning from the Causal Perspective
  ☆29Updated last year
• slingling / MS-HGAT
  Implementation of AAAI22 paper: MS-HGAT: Memory-enhanced Sequential Hypergraph Attention Network for Information Diffusion Prediction
  ☆43Updated 2 years ago
• SongtaoLiu0823 / LAGNN
  [ICML 2022] Local Augmentation for Graph Neural Networks
  ☆66Updated last year
• Wuyxin / DIR-GNN
  (ICLR 2022) Discovering Invariant Rationales for Graph Neural Networks
  ☆133Updated 2 years ago