Editing Laplacian matrix (section)

== Application software ==
* [[scikit-learn]] Spectral Clustering<ref>{{Cite web|url=https://scikit-learn.org/stable/modules/clustering.html#spectral-clustering|title=2.3. Clustering}}</ref>
* PyGSP: Graph Signal Processing in Python<ref>{{Cite web|url=https://github.com/epfl-lts2/pygsp|title = PyGSP: Graph Signal Processing in Python|website = [[GitHub]]|date = 23 March 2022}}</ref>
* megaman: Manifold Learning for Millions of Points<ref>{{Cite web|url=https://github.com/mmp2/megaman|title = Megaman: Manifold Learning for Millions of Points|website = [[GitHub]]|date = 14 March 2022}}</ref>
* smoothG<ref>{{Cite web|url=https://github.com/LLNL/smoothG|title = SmoothG|website = [[GitHub]]|date = 17 September 2020}}</ref>
* Laplacian Change Point Detection for Dynamic Graphs (KDD 2020)<ref>{{Cite web|url=https://complexdatalabmcgill.github.io/papers/post-andy-kdd2020paper/|title=Announcing Our Paper at KDD 2020|date=2 July 2020 }}</ref>
* LaplacianOpt (A Julia Package for Maximizing Laplacian's Second Eigenvalue of Weighted Graphs) <ref>{{Cite web|url=https://github.com/harshangrjn/LaplacianOpt.jl|title = Harshangrjn/LaplacianOpt.jl|website = [[GitHub]]|date = 2 February 2022}}</ref>
* LigMG (Large Irregular Graph MultiGrid)<ref>{{Cite web|url=https://github.com/ligmg/ligmg|title=LigMG (Large Irregular Graph MultiGrid)-- A distributed memory graph Laplacian solver for large irregular graphs|website=[[GitHub]]|date=5 January 2022}}</ref>
* Laplacians.jl<ref>{{Cite web|url=https://github.com/danspielman/Laplacians.jl|title = Laplacians.jl|website = [[GitHub]]|date = 11 March 2022}}</ref>