microsoft / GraphormerLinks
Graphormer is a general-purpose deep learning backbone for molecular modeling.
☆2,286Updated 11 months ago
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.☆967Updated 3 years ago
- Graph Transformer Networks (Authors' PyTorch implementation for the NeurIPS 19 paper)☆1,027Updated 2 years ago
- Strategies for Pre-training Graph Neural Networks☆1,014Updated last year
- Benchmark datasets, data loaders, and evaluators for graph machine learning☆2,008Updated 3 weeks ago
- Recipe for a General, Powerful, Scalable Graph Transformer☆738Updated 10 months ago
- Platform for designing and evaluating Graph Neural Networks (GNN)☆1,800Updated last year
- Repository for benchmarking graph neural networks (JMLR 2023)☆2,587Updated last year
- A library for graph deep learning research☆1,956Updated 10 months ago
- Papers about graph transformers.☆880Updated 2 months ago
- Code for "Heterogeneous Graph Transformer" (WWW'20), which is based on pytorch_geometric☆834Updated last year
- Papers about pretraining and self-supervised learning on Graph Neural Networks (GNN).☆1,678Updated last year
- Universal Graph Transformer Self-Attention Networks (TheWebConf WWW 2022) (Pytorch and Tensorflow)☆670Updated 2 years ago
- PyGCL: A PyTorch Library for Graph Contrastive Learning☆945Updated 10 months ago
- How Powerful are Graph Neural Networks?☆1,217Updated 3 years ago
- gnn explainer☆957Updated 9 months ago
- Graph Attention Networks (https://arxiv.org/abs/1710.10903)☆3,361Updated 3 years ago
- Simple reference implementation of GraphSAGE.☆1,022Updated 5 years ago
- Source code of Graph-Bert☆494Updated last year
- Pytorch implementation of the Graph Attention Network model by Veličković et. al (2017, https://arxiv.org/abs/1710.10903)☆3,035Updated last year
- CogDL: A Comprehensive Library for Graph Deep Learning (WWW 2023)☆1,777Updated last year
- [NeurIPS 2020] "Graph Contrastive Learning with Augmentations" by Yuning You, Tianlong Chen, Yongduo Sui, Ting Chen, Zhangyang Wang, Yang…☆593Updated 10 months ago
- Pytorch Repo for DeepGCNs (ICCV'2019 Oral, TPAMI'2021), DeeperGCN (arXiv'2020) and GNN1000(ICML'2021): https://www.deepgcns.org☆1,160Updated 2 years ago
- Papers about explainability of GNNs☆733Updated 3 weeks ago
- Code for the paper "How Attentive are Graph Attention Networks?" (ICLR'2022)☆335Updated 3 years ago
- GraphMAE: Self-Supervised Masked Graph Autoencoders in KDD'22☆518Updated 2 years ago
- Pytorch Geometric Tutorials☆1,110Updated 2 years ago
- PyTorch Implementation and Explanation of Graph Representation Learning papers: DeepWalk, GCN, GraphSAGE, ChebNet & GAT.☆1,195Updated 2 months ago
- official implementation for the paper "Simplifying Graph Convolutional Networks"☆842Updated 3 years ago
- Hyperbolic Graph Convolutional Networks in PyTorch.☆622Updated 10 months ago
- Hypergraph Neural Networks (AAAI 2019)☆754Updated 2 years ago