HazyResearch / hgcnLinks
Hyperbolic Graph Convolutional Networks in PyTorch.
☆636Updated last year
Alternatives and similar repositories for hgcn
Users that are interested in hgcn are comparing it to the libraries listed below
Sorting:
- Official Repository of "A Fair Comparison of Graph Neural Networks for Graph Classification", ICLR 2020☆395Updated last year
- Deep Graph Infomax (https://arxiv.org/abs/1809.10341)☆646Updated 2 years ago
- Hyperbolic Graph Neural Networks☆237Updated 5 years ago
- Universal Graph Transformer Self-Attention Networks (TheWebConf WWW 2022) (Pytorch and Tensorflow)☆674Updated 3 years ago
- ☆300Updated 3 years ago
- Framework for evaluating Graph Neural Network models on semi-supervised node classification task☆477Updated 6 years ago
- Code for KDD'20 "Generative Pre-Training of Graph Neural Networks"☆496Updated last year
- This is a Pytorch implementation of paper: DropEdge: Towards Deep Graph Convolutional Networks on Node Classification☆471Updated 2 years ago
- ☆495Updated 4 years ago
- Code for "Heterogeneous Graph Transformer" (WWW'20), which is based on pytorch_geometric☆858Updated last year
- Implementation of Principal Neighbourhood Aggregation for Graph Neural Networks in PyTorch, DGL and PyTorch Geometric☆353Updated 2 months ago
- PPNP & APPNP models from "Predict then Propagate: Graph Neural Networks meet Personalized PageRank" (ICLR 2019)☆322Updated 8 months ago
- official implementation for the paper "Simplifying Graph Convolutional Networks"☆845Updated 3 years ago
- Official code for "InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization" …☆318Updated last year
- This repository implements variational graph auto encoder by Thomas Kipf.☆413Updated 3 years ago
- Source code and dataset of the NeurIPS 2020 paper "Graph Random Neural Network for Semi-Supervised Learning on Graphs"☆211Updated 2 years ago
- Papers about developing deep Graph Neural Networks (GNNs)☆301Updated 2 years ago
- Graph Diffusion Convolution, as proposed in "Diffusion Improves Graph Learning" (NeurIPS 2019)☆272Updated 2 years ago
- Strategies for Pre-training Graph Neural Networks☆1,030Updated 2 years ago
- Graph Auto-Encoder in PyTorch☆439Updated last year
- Hierarchical Graph Pooling with Structure Learning☆342Updated 4 years ago
- ICLR 2020: Composition-Based Multi-Relational Graph Convolutional Networks☆624Updated last year
- [ICLR 2020; IPDPS 2019] Fast and accurate minibatch training for deep GNNs and large graphs (GraphSAINT: Graph Sampling Based Inductive L…☆493Updated 3 years ago
- ☆357Updated last year
- gnn explainer☆987Updated 11 months ago
- [NeurIPS 2020] "Graph Contrastive Learning with Augmentations" by Yuning You, Tianlong Chen, Yongduo Sui, Ting Chen, Zhangyang Wang, Yang…☆602Updated last year
- Representation learning on dynamic graphs using self-attention networks☆296Updated 2 years ago
- [ICLR 2021] Combining Label Propagation and Simple Models Out-performs Graph Neural Networks (https://arxiv.org/abs/2010.13993)☆289Updated 4 years ago
- A curated list for awesome self-supervised learning for graphs.☆388Updated 2 years ago
- Graph Transformer Networks (Authors' PyTorch implementation for the NeurIPS 19 paper)☆1,039Updated 2 years ago