graph-structure-learning 0.1.2

Extracting graphs from signals on nodes

Graph learning

Collection of models for learning networks from signals.

Clustering methods follow the sklearn API.

Installation

Clone the git repository and install with pip:

git clone https://github.com/LTS4/graph-learning.git
cd graph-learning
pip install .

References

Base Models

Smooth learning (LogModel)

V. Kalofolias, “How to Learn a Graph from Smooth Signals,” in Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, May 2016, pp. 920–929. https://doi.org/10.48550/arXiv.1601.02513.

V. Kalofolias and N. Perraudin, “Large Scale Graph Learning From Smooth Signals,” presented at the International Conference on Learning Representations, Sep. 2018. Available: https://openreview.net/forum?id=ryGkSo0qYm

Part of the code is ported to Python from the Matlab implementation from https://github.com/epfl-lts2/gspbox, published under GNU General Public License v3.0.

LGRMF

H. E. Egilmez, E. Pavez, and A. Ortega, “Graph learning with Laplacian constraints: Modeling attractive Gaussian Markov random fields,” in 2016 50th Asilomar Conference on Signals, Systems and Computers, Nov. 2016, pp. 1470–1474. https://doi.org/10.1109/ACSSC.2016.7869621.

Clustering models

GLMM

H. P. Maretic and P. Frossard, “Graph Laplacian Mixture Model,” IEEE Transactions on Signal and Information Processing over Networks, vol. 6, pp. 261–270, 2020, https://doi.org/10.1109/TSIPN.2020.2983139.

k-Graphs

H. Araghi, M. Sabbaqi, and M. Babaie–Zadeh, “$K$-Graphs: An Algorithm for Graph Signal Clustering and Multiple Graph Learning,” IEEE Signal Processing Letters, vol. 26, no. 10, pp. 1486–1490, Oct. 2019, https://doi.org/10.1109/LSP.2019.2936665.

Temporal graph learning

TGFA

K. Yamada, Y. Tanaka, and A. Ortega, “Time-Varying Graph Learning with Constraints on Graph Temporal Variation,” Jan. 10, 2020, https://doi.org/10.48550/arXiv.2001.03346.

Temporal Multiresolution Graph Learning (GraphDictHier)

K. Yamada and Y. Tanaka, “Temporal Multiresolution Graph Learning,” IEEE Access, vol. 9, pp. 143734–143745, 2021, https://doi.org/10.1109/ACCESS.2021.3120994.

Dictionary Models

Parametric Dictionary Learning (GraphDictSpectral)

D. Thanou, D. I. Shuman, and P. Frossard, “Parametric dictionary learning for graph signals,” in 2013 IEEE Global Conference on Signal and Information Processing, Dec. 2013, pp. 487–490. https://doi.org/10.1109/GlobalSIP.2013.6736921.

Graph Dictionary Signal Model (GraphDictLog, GraphDictBase)

W. Cappelletti and P. Frossard, “Graph-Dictionary Signal Model for Sparse Representations of Multivariate Data,” Nov. 08, 2024, arXiv:2411.05729