Machine Learning for GraphsApply
We have numerous projects where we work networks or graphs of various kinds, biological ones in particular. Networks can be undirected, directed with or without signs, discrete or continuous.
For publications see google scholar (https://scholar.google.com/citations hl=sv&user=_DUppAgAAAAJ&view_op=list_works&sortby=pubdate).
Challenges and sub-projects include:-
How to compare 2 and several networks,review,benchmark current methods, invent new efficient algorithms for network comparison
-Analyze networks embedded in hyperbolicspace
-Review, benchmark current methods for embedding networks into anML framework
-Generative modeling of networks constrained by correlational information from data-sets
-Partially overlapping networks,analyzetheirputativealignment,constructionof multi-layer networks from several partially overlappinggraphs.
-Search and propagation in multi-layernetworks
-Alignment of several but different real protein interaction networks