dmlc--dgl
Zihao Ye
650f6ee1e0
* gat * upd * upd sage * upd * upd * upd * upd * upd * add gmmconv * upd ggnn * upd * upd * upd * upd * add citation examples * add README * fix cheb * improve doc * formula * upd * trigger * lint * lint * upd * add test for transform * add test * check * upd * improve doc * shape check * upd * densechebconv, currently not correct (?) * fix cheb * fix * upd * upd sgc-reddit * upd * trigger
28 行
737 B
Markdown
28 行
737 B
Markdown
Inductive Representation Learning on Large Graphs (GraphSAGE)
|
|
============
|
|
|
|
- Paper link: [http://papers.nips.cc/paper/6703-inductive-representation-learning-on-large-graphs.pdf](http://papers.nips.cc/paper/6703-inductive-representation-learning-on-large-graphs.pdf)
|
|
- Author's code repo: [https://github.com/williamleif/graphsage-simple](https://github.com/williamleif/graphsage-simple). Note that the original code is
|
|
simple reference implementation of GraphSAGE.
|
|
|
|
Requirements
|
|
------------
|
|
- requests
|
|
|
|
``bash
|
|
pip install requests
|
|
``
|
|
|
|
|
|
Results
|
|
-------
|
|
|
|
Run with following (available dataset: "cora", "citeseer", "pubmed")
|
|
```bash
|
|
python3 graphsage.py --dataset cora --gpu 0
|
|
```
|
|
|
|
* cora: ~0.8330
|
|
* citeseer: ~0.7110
|
|
* pubmed: ~0.7830
|