Alternatives and similar repositories for awesome-GNN4TDL:

Users that are interested in awesome-GNN4TDL are comparing it to the libraries listed below

• TimeLovercc / Awesome-Graph-Causal-Learning
  A list of Graph Causal Learning materials.
  ☆194Updated 2 months ago
• zepengzhang / awesome-graph-structure-learning
  A collection of papers on Graph Structural Learning (GSL)
  ☆54Updated last year
• EdisonLeeeee / MaskGAE
  [KDD 2023] What’s Behind the Mask: Understanding Masked Graph Modeling for Graph Autoencoders
  ☆84Updated 5 months ago
• YesLab-Code / HTGNN
  ☆52Updated 3 years ago
• chirag-agarwall / nifty
  Code for paper https://arxiv.org/abs/2102.13186
  ☆44Updated 4 years ago
• yongduosui / CAL
  [KDD 2022] "Causal Attention for Interpretable and Generalizable Graph Classification" by Yongduo Sui, Xiang Wang, Jiancan Wu, Min Lin, X…
  ☆88Updated last year
• yueliu1999 / KAN4Graph
  Kolmogorov Arnold Networks (KANs) for Graph Neural Networks (GNNs) and Tasks on Graphs
  ☆58Updated 6 months ago
• wwweiwei / awesome-self-supervised-learning-for-tabular-data
  A collection of research materials on SSL for non-sequential tabular data (SSL4NSTD)
  ☆185Updated 2 months ago
• mims-harvard / GraphXAI
  GraphXAI: Resource to support the development and evaluation of GNN explainers
  ☆185Updated 10 months ago
• YuanchenBei / Awesome-Graph-Structure-Learning
  A curated list of papers on graph structure learning (GSL).
  ☆48Updated 3 months ago
• HaitaoMao / Awesome_Graph_Foundation_Models
  Accompanied repositories for our paper Graph foundation model
  ☆198Updated 5 months ago
• LARS-research / TabGNN
  ☆49Updated 3 years ago
• azminewasi / Awesome-Graph-Research-ICLR2024
  It is a comprehensive resource hub compiling all graph papers accepted at the International Conference on Learning Representations (ICLR)…
  ☆89Updated 5 months ago
• meettyj / HGMAE
  Code & data for AAAI'23 Oral paper "Heterogeneous Graph Masked Autoencoders".
  ☆58Updated 2 years ago
• xkLi-Allen / Awesome-GNN-in-LLMs-Papers
  ☆28Updated 4 months ago
• AntonioLonga / Explaining-the-Explainers-in-Graph-Neural-Networks
  Repository associated to the paper: "Explaining the Explainers in Graph Neural Networks: a Comparative Study"
  ☆35Updated last year
• MGitHubL / Awesome-Temporal-Graph-Learning
  Awesome Temporal Graph Learning is a collection of SOTA, novel temporal graph learning methods (papers, codes, and datasets).
  ☆68Updated 6 months ago
• usail-hkust / Awesome-Causality-Inspired-GNNs
  An awesome collection of causality-inspired graph neural networks.
  ☆72Updated 4 months ago
• doujiang-zheng / Dynamic-Temporal-Graph-Learning-Reading-List
  Advances on machine learning of dynamic (temporal) graphs, covering the reading list of recent top academic conferences.
  ☆58Updated last year
• Xtra-Computing / Awesome-Literature-ILoGs
  Awesome literature on imbalanced learning on graphs
  ☆75Updated 7 months ago
• pygod-team / data
  Data repository for PyGOD
  ☆41Updated last year
• MatteoSalvatori / INCE
  Interaction Network Contextual Embedding
  ☆15Updated 9 months ago
• CongWeilin / GraphMixer
  ☆99Updated last year
• logseminar / Schedule
  Schedule for learning on graphs seminar
  ☆109Updated last year
• YuanchenBei / Awesome-Pretraining-for-Graph-Neural-Networks
  A curated list of papers on pre-training for graph neural networks (Pre-train4GNN).
  ☆193Updated 3 months ago
• zyzisastudyreallyhardguy / Graph-Group-Discrimination
  Code for NeurIPS 2022 paper "Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group Discriminat…
  ☆55Updated 2 years ago
• THUMNLab / awesome-graph-ood
  Papers about out-of-distribution generalization on graphs.
  ☆167Updated last year
• sunxiaobei / awesome-attention-based-gnns
  A collection of resources on attention-based graph neural networks
  ☆70Updated last year
• yihongma / CILG-Papers
  A curated list of papers and code related to class-imbalanced learning on graphs (CILG).
  ☆39Updated 3 months ago
• kaize0409 / awesome-graph-data-augmentaion
  A curated list of publications and code about data augmentaion for graphs.
  ☆64Updated 2 years ago