Statements (59)
| Predicate | Object |
|---|---|
| gptkbp:instance_of |
gptkb:Library
|
| gptkbp:dependency |
gptkb:torch-cluster
gptkb:torch-scatter gptkb:torch-sparse gptkb:torch-geometric-temporal gptkb:Py_Torch |
| gptkbp:developed_by |
Py Torch community
|
| gptkbp:first_released |
gptkb:2017
|
| gptkbp:has_community |
active user community
|
| gptkbp:has_documentation |
online documentation
|
| gptkbp:has_feature |
data augmentation
pre-trained models dynamic graphs graph visualization community detection multi-GPU support custom layers mini-batch training link prediction graph classification node classification graph attention networks graph generation graph pooling graph-based anomaly detection graph-based clustering graph-based feature extraction graph-based recommendation systems graph embedding graph sampling spatial-temporal graphs graph neural network layers graph-based multi-task learning graph-based reinforcement learning graph-based semi-supervised learning graph-based supervised learning graph-based transfer learning graph-based unsupervised learning |
| https://www.w3.org/2000/01/rdf-schema#label |
torch-geometric
|
| gptkbp:is_a_hub_for |
https://github.com/pyg-team/pytorch_geometric
|
| gptkbp:is_compatible_with |
gptkb:Graphics_Processing_Unit
gptkb:Sci_Py gptkb:Num_Py |
| gptkbp:is_used_for |
graph neural networks
|
| gptkbp:latest_version |
gptkb:2023
|
| gptkbp:license |
MIT License
|
| gptkbp:provides |
tutorials
examples benchmarking tools graph convolutional networks data loaders message passing framework |
| gptkbp:supports |
gptkb:Py_Torch
heterogeneous graphs attributed graphs temporal graphs |
| gptkbp:written_in |
gptkb:Library
|
| gptkbp:bfsParent |
gptkb:Py_Torch_Geometric
|
| gptkbp:bfsLayer |
5
|