ENH: Adding Graph Embedding Functionality to SciPy
Hi all, I’m curious whether the development team would be interested in the addition of graph embedding functionality, specifically adding Adjacency<https://doi.org/10.1080/01621459.2012.699795>/Laplacian<https://projecteuclid.org/euclid.aos/1534492839> spectral embedding to scipy.sparse.csgraph (or anywhere else it would make sense to have it). Both methods are useful in a variety of graph applications, such as clustering nodes with similar connective structure; in essence, they both amount to an SVD. Our current implementations in GraSPy<https://graspy.neurodata.io/tutorials/embedding/adjacencyspectralembed>, (available at ASE<https://github.com/neurodata/graspy/blob/ase-embed/graspy/embed/ase.py> and LSE<https://github.com/neurodata/graspy/blob/ase-embed/graspy/embed/lse.py>) input a graph represented as a dense or sparse matrix, and return the appropriate embedding. Please let me know if you'd like to add these functions to scipy. Best, Ali Saad-Eldin
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Ali Saad-Eldin