Alternatives and similar repositories for GTOT-Tuning

Users that are interested in GTOT-Tuning are comparing it to the libraries listed below

• RPaolino / loopy
  ☆11Updated last year
• czczup / GPTrans
  [IJCAI 2023] Graph Propagation Transformer for Graph Representation Learning
  ☆50Updated 2 years ago
• DeepGraphLearning / GraphLoG
  Implementation of Self-supervised Graph-level Representation Learning with Local and Global Structure (ICML 2021).
  ☆80Updated 4 years ago
• SDS-Lab / ROT-Pooling
  Learnable Global Pooling Layers Based on Regularized Optimal Transport (ROT)
  ☆16Updated last year
• shamim-hussain / egt
  Edge-Augmented Graph Transformer
  ☆51Updated 3 years ago
• harryjo97 / EHGNN
  Official Code Repository for the paper "Edge Representation Learning with Hypergraphs" (NeurIPS 2021)
  ☆53Updated 2 years ago
• LingxiaoShawn / GNNAsKernel
  Source code for From Stars to Subgraphs (ICLR 2022)
  ☆71Updated last year
• lenscloth / GRPE
  Official Implementation of "GRPE: Relative Positional Encoding for Graph Transformer"
  ☆61Updated 3 years ago
• liugangcode / Data-Centric-Transfer
  [NeurIPS'23] Source code of "Data-Centric Learning from Unlabeled Graphs with Diffusion Model": A data-centric transfer learning framewor…
  ☆22Updated 5 months ago
• jw9730 / ehnn
  [ECCV'22] Equivariant Hypergraph Neural Networks, in PyTorch
  ☆30Updated 2 years ago
• ha-lins / PGCL
  The code of “Prototypical Graph Contrastive Learning”. [TNNLS 2022]
  ☆24Updated 3 years ago
• weitianxin / HyperGCL
  [NeurIPS 2022] "Augmentations in Hypergraph Contrastive Learning: Fabricated and Generative" by Tianxin Wei, Yuning You, Tianlong Chen, Y…
  ☆61Updated 3 years ago
• googlebaba / DisC
  NeurIPS2022-Debiasing Graph Neural Networks via Learning Disentangled Causal Substructure
  ☆42Updated 2 years ago
• NeXAIS / DDM
  Directional diffusion models
  ☆43Updated last year
• ucbrise / graphtrans
  Representing Long-Range Context for Graph Neural Networks with Global Attention
  ☆130Updated 3 years ago
• YuGuangWang / UFG
  ☆36Updated 3 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…
  ☆55Updated last year
• BorgwardtLab / NeuralWalker
  Official Pytorch implementation of NeuralWalker (ICLR 2025)
  ☆36Updated 4 months ago
• snap-research / MLPInit-for-GNNs
  [ICLR 2023] MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP Initialization
  ☆77Updated 2 years ago
• hedongxiao-tju / BM-GCN
  The code of paper "Block Modeling-Guided Graph Convolutional Neural Networks".
  ☆33Updated 3 years ago
• HICAI-ZJU / iMoLD
  Official implementation for Learning Invariant Molecular Representation in Latent Discrete Space (NeurIPS 2023)
  ☆22Updated 2 years ago
• ndey96 / GCNN-Explainability
  Implementation of "Explainability Methods for Graph Convolutional Neural Networks" from HRL Laboratories
  ☆84Updated 4 years ago
• BenGutteridge / DRew
  ☆31Updated last year
• kanz76 / GMPNN-CS
  ☆29Updated last year
• JinheonBaek / GMT
  Official Code Repository for the paper "Accurate Learning of Graph Representations with Graph Multiset Pooling" (ICLR 2021)
  ☆107Updated 3 years ago
• GRAPH-0 / GraphGDP
  Implementation for the paper: GraphGDP: Generative Diffusion Processes for Permutation Invariant Graph Generation
  ☆30Updated 2 years ago
• kilianhae / discrete_DPPM_Graphs
  Diffusion Models for Graphs Benefit From Discrete State Spaces
  ☆33Updated 2 years ago
• CheriseZhu / GIL
  The implementation of our NeurIPS 2020 paper "Graph Geometry Interaction Learning" (GIL)
  ☆46Updated 5 years ago
• liugangcode / SGIR
  [KDD'23] Source codes of "Semi-Supervised Graph Imbalanced Regression"
  ☆22Updated 4 months ago
• LFhase / GALA
  [NeurIPS 2023] Does Invariant Graph Learning via Environment Augmentation Learn Invariance?
  ☆22Updated last year