Implementation of latest graph neural network model using Pytorch and torch_geometric.
BaseDataLoader
BaseModel
BaseTrainer
Various neural network layer for graph neural network
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SGC_LL
: Adaptive Graph Convolutional Neural Networks. Ruoyu Li, Sheng Wang, Feiyun Zhu, Junzhou Huang. AAAI 2018. paper -
graph_max_pool
: same as above
Customized data loaders for various datasets
AlchemyDataLoader
: Tecent Alchemy dataset
The state-of-the-art graph neural network model
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AGCN
: Adaptive Graph Convolutional Neural Networks. Ruoyu Li, Sheng Wang, Feiyun Zhu, Junzhou Huang. AAAI 2018. paper -
MPNN
: Neural Message Passing for Quantum Chemistry. Gilmer, Justin and Schoenholz, Samuel S and Riley, Patrick F and Vinyals, Oriol and Dahl, George E. 2017. paper
Customized trainer for training the model and save the training log
Trainer
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
Please make sure to update tests as appropriate.
- Implement common feature transformation for molecular graph
- Multi-GPU support