Alternatives and similar repositories for GMT

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

• harryjo97 / EHGNN
  Official Code Repository for the paper "Edge Representation Learning with Hypergraphs" (NeurIPS 2021)
  ☆53Updated 2 years ago
• dongkwan-kim / SuperGAT
  [ICLR 2021] How to Find Your Friendly Neighborhood: Graph Attention Design with Self-Supervision
  ☆159Updated 2 years ago
• mims-harvard / G-Meta
  Graph meta learning via local subgraphs (NeurIPS 2020)
  ☆126Updated last year
• GemsLab / H2GCN
  Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)
  ☆105Updated 2 months ago
• susheels / adgcl
  Adversarial Graph Augmentation to Improve Graph Contrastive Learning
  ☆89Updated 3 years ago
• Shen-Lab / GraphCL_Automated
  [ICML 2021] "Graph Contrastive Learning Automated" by Yuning You, Tianlong Chen, Yang Shen, Zhangyang Wang; [WSDM 2022] "Bringing Yo…
  ☆113Updated 11 months ago
• LingxiaoShawn / GNNAsKernel
  Source code for From Stars to Subgraphs (ICLR 2022)
  ☆69Updated last year
• ucbrise / graphtrans
  Representing Long-Range Context for Graph Neural Networks with Global Attention
  ☆130Updated 3 years ago
• snap-stanford / GIB
  Graph Information Bottleneck (GIB) for learning minimal sufficient structural and feature information using GNNs
  ☆137Updated 2 years ago
• danielegrattarola / SRC
  Code for "Understanding Pooling in Graph Neural Networks" (TNNLS 2022).
  ☆62Updated 3 years ago
• AaltoPML / Rethinking-pooling-in-GNNs
  ☆62Updated 4 years ago
• DeepGraphLearning / GraphLoG
  Implementation of Self-supervised Graph-level Representation Learning with Local and Global Structure (ICML 2021).
  ☆80Updated 4 years ago
• jianhao2016 / GPRGNN
  ☆135Updated 2 years ago
• yzjiao / Subg-Con
  Code for ICDM2020 full paper: "Sub-graph Contrast for Scalable Self-Supervised Graph Representation Learning"
  ☆45Updated 3 years ago
• junxia97 / SimGRACE
  [WWW 2022] "SimGRACE: A Simple Framework for Graph Contrastive Learning without Data Augmentation"
  ☆81Updated 3 years ago
• mengliu1998 / DL4DisassortativeGraphs
  Papers about developing DL methods on disassortative graphs
  ☆48Updated 3 years ago
• vijaydwivedi75 / gnn-lspe
  Source code for GNN-LSPE (Graph Neural Networks with Learnable Structural and Positional Representations), ICLR 2022
  ☆264Updated 3 years ago
• gasteigerjo / gdc
  Graph Diffusion Convolution, as proposed in "Diffusion Improves Graph Learning" (NeurIPS 2019)
  ☆272Updated 2 years ago
• Namkyeong / BGRL_Pytorch
  Pytorch implementation of "Large-Scale Representation Learning on Graphs via Bootstrapping"
  ☆81Updated 3 years ago
• zpeng27 / GMI
  Graph Representation Learning via Graphical Mutual Information Maximization
  ☆117Updated 5 years ago
• muhanzhang / NestedGNN
  ☆57Updated 3 years ago
• tech-srl / bottleneck
  Code for the paper: "On the Bottleneck of Graph Neural Networks and Its Practical Implications"
  ☆95Updated 3 years ago
• DevinKreuzer / SAN
  ☆155Updated 4 years ago
• jianhao2016 / AllSet
  This is the GitHub repository for our ICLR22 paper: "You are AllSet: A Multiset Function Framework for Hypergraph Neural Networks"
  ☆100Updated 2 years ago
• balcilar / gnn-matlang
  Code of "Breaking the Limits of Message Passing Graph Neural Networks" paper published in ICML2021
  ☆41Updated 4 years ago
• ahxt / g-mixup
  [ICML2022] G-Mixup: Graph Data Augmentation for Graph Classification
  ☆106Updated last year
• SongtaoLiu0823 / LAGNN
  [ICML 2022] Local Augmentation for Graph Neural Networks
  ☆65Updated last year
• ChandlerBang / GCond
  [ICLR'22] [KDD'22] [IJCAI'24] Implementation of "Graph Condensation for Graph Neural Networks"
  ☆140Updated 9 months ago
• zhao-tong / GAug
  AAAI'21: Data Augmentation for Graph Neural Networks
  ☆193Updated last year
• BorgwardtLab / SAT
  Official Pytorch code for Structure-Aware Transformer.
  ☆258Updated 2 years ago