Skip to content

Latest commit

 

History

History
23 lines (15 loc) · 848 Bytes

README.md

File metadata and controls

23 lines (15 loc) · 848 Bytes

A naive Python implementation of the NeurIPS paper: Structured Graph Learning (SGL) algorithm by Kumar et. al (2019, https://papers.nips.cc/paper/9339-structured-graph-learning-via-laplacian-spectral-constraints)

Work in Progress!

learn k-component graph

Currently only learn_k_component_graph API is available from sgl library. Load the dataset in main.py. Currently two moon dataset is there. Others are coming sooner!

python main.py

plots are generated in the directory plots

learn Bipartite graph

Coming Soon!

License

MIT LICENSE

See LICENSE