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] |