microsoft / GraphormerLinks
Graphormer is a general-purpose deep learning backbone for molecular modeling.
☆2,342Updated last year
Alternatives and similar repositories for Graphormer
Users that are interested in Graphormer are comparing it to the libraries listed below
Sorting:
- Graph Transformer Architecture. Source code for "A Generalization of Transformer Networks to Graphs", DLG-AAAI'21.☆994Updated 4 years ago
- Benchmark datasets, data loaders, and evaluators for graph machine learning☆2,032Updated 4 months ago
- Strategies for Pre-training Graph Neural Networks☆1,036Updated 2 years ago
- Repository for benchmarking graph neural networks (JMLR 2023)☆2,620Updated 2 years ago
- Graph Transformer Networks (Authors' PyTorch implementation for the NeurIPS 19 paper)☆1,048Updated 2 years ago
- Papers about pretraining and self-supervised learning on Graph Neural Networks (GNN).☆1,684Updated last year
- Recipe for a General, Powerful, Scalable Graph Transformer☆770Updated last year
- Papers about graph transformers.☆907Updated 5 months ago
- Platform for designing and evaluating Graph Neural Networks (GNN)☆1,831Updated last year
- A library for graph deep learning research☆1,984Updated last year
- Graph Attention Networks (https://arxiv.org/abs/1710.10903)☆3,413Updated 3 years ago
- gnn explainer☆995Updated last year
- CogDL: A Comprehensive Library for Graph Deep Learning (WWW 2023)☆1,795Updated last year
- Pytorch implementation of the Graph Attention Network model by Veličković et. al (2017, https://arxiv.org/abs/1710.10903)☆3,061Updated 2 years ago
- Universal Graph Transformer Self-Attention Networks (TheWebConf WWW 2022) (Pytorch and Tensorflow)☆675Updated 3 years ago
- Code for "Heterogeneous Graph Transformer" (WWW'20), which is based on pytorch_geometric☆865Updated last year
- PyGCL: A PyTorch Library for Graph Contrastive Learning☆948Updated last year
- How Powerful are Graph Neural Networks?☆1,243Updated 4 years ago
- Pytorch Geometric Tutorials☆1,130Updated 2 years ago
- Simple reference implementation of GraphSAGE.☆1,030Updated 5 years ago
- Hypergraph Neural Networks (AAAI 2019)☆779Updated 3 years ago
- Representation learning on large graphs using stochastic graph convolutions.☆3,582Updated last year
- Pytorch Repo for DeepGCNs (ICCV'2019 Oral, TPAMI'2021), DeeperGCN (arXiv'2020) and GNN1000(ICML'2021): https://www.deepgcns.org☆1,177Updated 3 years ago
- A PyTorch implementation of GraphSAGE. This package contains a PyTorch implementation of GraphSAGE.☆663Updated last year
- Hyperbolic Graph Convolutional Networks in PyTorch.☆642Updated last year
- A PyTorch implementation of "SimGNN: A Neural Network Approach to Fast Graph Similarity Computation" (WSDM 2019).☆798Updated 2 years ago
- Graph Convolutional Networks in PyTorch☆5,348Updated 4 years ago
- Code for the paper "How Attentive are Graph Attention Networks?" (ICLR'2022)☆345Updated 3 years ago
- TGN: Temporal Graph Networks☆1,099Updated last year
- My implementation of the original GAT paper (Veličković et al.). I've additionally included the playground.py file for visualizing the Co…☆2,590Updated 2 years ago