Statements (54)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
gptkb:software
graph neural network library |
| gptkbp:basedOn |
gptkb:PyTorch
|
| gptkbp:citation |
gptkb:Fey,_M._&_Lenssen,_J._E._(2019)._Fast_Graph_Representation_Learning_with_PyTorch_Geometric._ICLR_Workshop.
|
| gptkbp:compatibleWith |
gptkb:PyTorch_Lightning
gptkb:scikit-learn DGL |
| gptkbp:developer |
gptkb:Jan_Eric_Lenssen
gptkb:Matthias_Fey |
| gptkbp:documentation |
https://pytorch-geometric.readthedocs.io/
|
| gptkbp:firstReleased |
2018
|
| gptkbp:hasComponent |
torch_geometric.benchmark
torch_geometric.data torch_geometric.datasets torch_geometric.deprecation torch_geometric.errors torch_geometric.experimental torch_geometric.explain torch_geometric.graphgym torch_geometric.io torch_geometric.loader torch_geometric.logging torch_geometric.nn torch_geometric.profile torch_geometric.sampler torch_geometric.seed torch_geometric.testing torch_geometric.transforms torch_geometric.typing torch_geometric.utils torch_geometric.version torch_geometric.visualization |
| https://www.w3.org/2000/01/rdf-schema#label |
PyTorch Geometric
|
| gptkbp:license |
gptkb:MIT_License
|
| gptkbp:maintainedBy |
gptkb:PyG_Team
|
| gptkbp:programmingLanguage |
gptkb:Python
|
| gptkbp:repository |
https://github.com/pyg-team/pytorch_geometric
|
| gptkbp:supports |
graph neural networks
CUDA acceleration dynamic graphs graph attention networks graph convolutional networks heterogeneous graphs message passing neural networks mini-batch training |
| gptkbp:usedFor |
gptkb:machine_learning
deep learning graph representation learning graph classification link prediction node classification |
| gptkbp:bfsParent |
gptkb:convolutional_neural_network
gptkb:Meta_AI |
| gptkbp:bfsLayer |
5
|