GNN Library GammGL
GammaGL(Gamma Graph Library), GAMMA LAB and Pengcheng Laboratory provide more than 20 mainstream classical models with the latest open-source graph neural network algorithm library
In addition, GammaGL is very similar to the mainstream PyTorch Geometric (PyG) interface design. GammaGL is based on TensorLayerXYou can develop it as a PyG that supports TensorFlow, Paddle, MindSpore, and switch back-end deep learning frameworks with one click.
Porject page:https://github.com/BUPT-GAMMA/GammaGL
At the same time, we provide more than twenty mainstream classical models for you to reuse.
| TensorFlow | PyTorch | Paddle | MindSpore | |
|---|---|---|---|---|
| GCN [ICLR 2017] | ||||
| GAT [ICLR 2018] | ||||
| GraphSAGE [NeurIPS 2017] | ||||
| ChebNet [NeurIPS 2016] | ||||
| GCNII [ICLR 2017] | ||||
| JKNet [ICML 2018] | ||||
| DiffPool [NeurIPS 2018] | ||||
| SGC [ICML 2019] | ||||
| GIN [ICLR 2019] | ||||
| APPNP [ICLR 2019] | ||||
| AGNN [arxiv] | ||||
| SIGN [ICML 2020 Workshop] | ||||
| DropEdge [ICLR 2020] | ||||
| GATv2 [ICLR 2021] | ||||
| GPRGNN [ICLR 2021] | ||||
| FAGCN [AAAI 2021] | ||||
| GNN-Film [PMLR 2020] | ||||
| GraphGAN [AAAI 2018] | ||||
| HardGAT [KDD 2019] | ||||
| MixHop [ICML 2019] | ||||
| PNA [NeurIPS 2020] | ||||
| GEN [WWW 2021] |
| Contrastive Learning | TensorFlow | PyTorch | Paddle | MindSpore |
|---|---|---|---|---|
| DGI [ICLR 2019] | ||||
| GRACE [ICML 2020 Workshop] | ||||
| MVGRL [ICML 2020] | ||||
| InfoGraph [ICLR 2020] | ||||
| MERIT [IJCAI 2021] |
| Heterogeneous Graph Learning | TensorFlow | PyTorch | Paddle | MindSpore |
|---|---|---|---|---|
| RGCN [ESWC2018] | ||||
| HAN [WWW 2019] | ||||
| HGT [WWW 2020] | ||||
| SimpleHGN [KDD 2021] |