weihua916 / powerful-gnns
How Powerful are Graph Neural Networks?
☆1,216Updated 3 years ago
Alternatives and similar repositories for powerful-gnns:
Users that are interested in powerful-gnns are comparing it to the libraries listed below
- Simple reference implementation of GraphSAGE.☆1,018Updated 4 years ago
- Deep Graph Infomax (https://arxiv.org/abs/1809.10341)☆640Updated 2 years ago
- A PyTorch implementation of GraphSAGE. This package contains a PyTorch implementation of GraphSAGE.☆647Updated last year
- ☆490Updated 4 years ago
- gnn explainer☆949Updated 8 months ago
- official implementation for the paper "Simplifying Graph Convolutional Networks"☆842Updated 3 years ago
- Benchmark datasets, data loaders, and evaluators for graph machine learning☆1,998Updated 4 months ago
- Repository for benchmarking graph neural networks (JMLR 2023)☆2,582Updated last year
- PyTorch Implementation and Explanation of Graph Representation Learning papers: DeepWalk, GCN, GraphSAGE, ChebNet & GAT.☆1,191Updated last month
- Papers on Graph neural network(GNN)☆764Updated last year
- Strategies for Pre-training Graph Neural Networks☆1,006Updated last year
- Graph Transformer Networks (Authors' PyTorch implementation for the NeurIPS 19 paper)☆1,024Updated 2 years ago
- Semi-supervised learning with graph embeddings☆918Updated 5 years ago
- This is a Pytorch implementation of paper: DropEdge: Towards Deep Graph Convolutional Networks on Node Classification☆470Updated 2 years ago
- Framework for evaluating Graph Neural Network models on semi-supervised node classification task☆474Updated 6 years ago
- Code for "Heterogeneous Graph Transformer" (WWW'20), which is based on pytorch_geometric☆828Updated last year
- Implementation of Graph Auto-Encoders in TensorFlow☆1,686Updated 5 years ago
- Keras implementation of the graph attention networks (GAT) by Veličković et al. (2017; https://arxiv.org/abs/1710.10903)☆487Updated 4 years ago
- Graph Attention Networks (https://arxiv.org/abs/1710.10903)☆3,347Updated 3 years ago
- Heterogeneous Graph Neural Network☆1,136Updated 5 years ago
- Papers about pretraining and self-supervised learning on Graph Neural Networks (GNN).☆1,668Updated last year
- Graph Convolutional Networks (GCNs)☆914Updated 7 years ago
- Code for EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs☆561Updated 3 years ago
- Pytorch implementation of the Graph Attention Network model by Veličković et. al (2017, https://arxiv.org/abs/1710.10903)☆3,027Updated last year
- GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models☆720Updated 3 years ago
- The sample codes for our ICLR18 paper "FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling""☆525Updated 4 years ago
- Official PyTorch Implementation of SAGPool - ICML 2019☆371Updated last year
- Platform for designing and evaluating Graph Neural Networks (GNN)☆1,795Updated last year
- A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019).☆799Updated 2 years ago
- Position-aware Graph Neural Networks☆399Updated 4 years ago