Alternatives and similar repositories for how_attentive_are_gats:

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

• BorgwardtLab / SAT
  Official Pytorch code for Structure-Aware Transformer.
  ☆252Updated last year
• daiquocnguyen / Graph-Transformer
  Universal Graph Transformer Self-Attention Networks (TheWebConf WWW 2022) (Pytorch and Tensorflow)
  ☆660Updated 2 years ago
• CRIPAC-DIG / GRACE
  [GRL+ @ ICML 2020] PyTorch implementation for "Deep Graph Contrastive Representation Learning" (https://arxiv.org/abs/2006.04131v2)
  ☆320Updated 9 months ago
• seongjunyun / Graph_Transformer_Networks
  Graph Transformer Networks (Authors' PyTorch implementation for the NeurIPS 19 paper)
  ☆1,001Updated last year
• DaehanKim / vgae_pytorch
  This repository implements variational graph auto encoder by Thomas Kipf.
  ☆397Updated 3 years ago
• Shen-Lab / GraphCL
  [NeurIPS 2020] "Graph Contrastive Learning with Augmentations" by Yuning You, Tianlong Chen, Yongduo Sui, Ting Chen, Zhangyang Wang, Yang…
  ☆570Updated 6 months ago
• sangyx / gtrick
  Bag of Tricks for Graph Neural Networks.
  ☆289Updated 6 months ago
• DropEdge / DropEdge
  This is a Pytorch implementation of paper: DropEdge: Towards Deep Graph Convolutional Networks on Node Classification
  ☆471Updated 2 years ago
• chennnM / GCNII
  PyTorch implementation of "Simple and Deep Graph Convolutional Networks"
  ☆341Updated 4 years ago
• THUDM / GRAND
  Source code and dataset of the NeurIPS 2020 paper "Graph Random Neural Network for Semi-Supervised Learning on Graphs"
  ☆209Updated last year
• vijaydwivedi75 / gnn-lspe
  Source code for GNN-LSPE (Graph Neural Networks with Learnable Structural and Positional Representations), ICLR 2022
  ☆250Updated 2 years ago
• HazyResearch / hgcn
  Hyperbolic Graph Convolutional Networks in PyTorch.
  ☆604Updated 6 months ago
• iMoonLab / DHGNN
  DHGNN source code for IJCAI19 paper: "Dynamic Hypergraph Neural Networks"
  ☆244Updated 2 years ago
• StatsDLMathsRecomSys / Inductive-representation-learning-on-temporal-graphs
  ☆305Updated 6 months ago
• zhao-tong / graph-data-augmentation-papers
  A curated list of graph data augmentation papers.
  ☆304Updated 9 months ago
• graphdeeplearning / graphtransformer
  Graph Transformer Architecture. Source code for "A Generalization of Transformer Networks to Graphs", DLG-AAAI'21.
  ☆924Updated 3 years ago
• rampasek / GraphGPS
  Recipe for a General, Powerful, Scalable Graph Transformer
  ☆699Updated 6 months ago
• aravindsankar28 / DySAT
  Representation learning on dynamic graphs using self-attention networks
  ☆287Updated last year
• zfjsail / gae-pytorch
  Graph Auto-Encoder in PyTorch
  ☆423Updated 10 months ago
• THUDM / GraphMAE
  GraphMAE: Self-Supervised Masked Graph Autoencoders in KDD'22
  ☆488Updated last year
• bingzhewei / geom-gcn
  ☆294Updated 2 years ago
• ucbrise / graphtrans
  Representing Long-Range Context for Graph Neural Networks with Global Attention
  ☆125Updated 2 years ago
• gasteigerjo / gdc
  Graph Diffusion Convolution, as proposed in "Diffusion Improves Graph Learning" (NeurIPS 2019)
  ☆268Updated last year
• zhumeiqiBUPT / AM-GCN
  AM-GCN: Adaptive Multi-channel Graph Convolutional Networks
  ☆232Updated 4 years ago
• lukecavabarrett / pna
  Implementation of Principal Neighbourhood Aggregation for Graph Neural Networks in PyTorch, DGL and PyTorch Geometric
  ☆345Updated 2 years ago
• dongkwan-kim / SuperGAT
  [ICLR 2021] How to Find Your Friendly Neighborhood: Graph Attention Design with Self-Supervision
  ☆155Updated last year
• LiuChuang0059 / graph-pooling-papers
  IJCAI‘23 Survey Track: Papers on Graph Pooling (GNN-Pooling)
  ☆113Updated last year
• microsoft / GraphFormers
  ☆115Updated 2 years ago
• acbull / GPT-GNN
  Code for KDD'20 "Generative Pre-Training of Graph Neural Networks"
  ☆491Updated 6 months ago
• kavehhassani / mvgrl
  ☆263Updated 2 years ago