| dmlc/dgl |
12,712 |
|
15 |
68 |
about 2 years ago |
449 |
December 08, 2023 |
470 |
apache-2.0 |
Python |
| Python package built to ease deep learning on graph, on top of existing DL frameworks. |
| aprbw/traffic_prediction |
237 |
|
0 |
0 |
over 2 years ago |
0 |
|
0 |
mit |
TeX |
| Traffic prediction is the task of predicting future traffic measurements (e.g. volume, speed, etc.) in a road network (graph), using historical data (timeseries). |
| beckdaniel/acl2018_graph2seq |
102 |
|
0 |
0 |
over 5 years ago |
0 |
|
3 |
apache-2.0 |
Python |
| Code for "Graph-to-Sequence Learning using Gated Graph Neural Networks" |
| jennyzhang0215/STAR-GCN |
63 |
|
0 |
0 |
almost 6 years ago |
0 |
|
0 |
|
Python |
| STAR-GCN: Stacked and Reconstructed Graph Convolutional Networks for Recommender Systems |
| Cartus/DCGCN |
43 |
|
0 |
0 |
over 6 years ago |
0 |
|
0 |
mit |
Python |
| Densely Connected Graph Convolutional Networks for Graph-to-Sequence Learning (authors' MXNet implementation for the TACL19 paper) |
| awslabs/sagemaker-graph-fraud-detection |
42 |
|
0 |
0 |
almost 5 years ago |
0 |
|
0 |
apache-2.0 |
Python |
| Use Amazon SageMaker and Deep Graph Library (DGL) for Fraud Detection in Networks |
| MengzhangLI/STFGNN |
12 |
|
0 |
0 |
about 5 years ago |
0 |
|
0 |
|
Python |
| Code of STFGNN@AAAI-2021 (Spatial-Temporal/ Traffic data forecasting) |
| jennyzhang0215/GaAN |
11 |
|
0 |
0 |
over 6 years ago |
0 |
|
3 |
|
Python |
| pierric/fei-nn |
8 |
|
0 |
0 |
over 3 years ago |
4 |
May 03, 2018 |
1 |
bsd-3-clause |
Haskell |
| High level APIs for leaveraging neural networks with MXNet in Haskell |
