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Spectral Inference Methods on Sparse Graphs: Theory and Applications
[article]
2016
arXiv
pre-print
In an era of unprecedented deluge of (mostly unstructured) data, graphs are proving more and more useful, across the sciences, as a flexible abstraction to capture complex relationships between complex objects. One of the main challenges arising in the study of such networks is the inference of macroscopic, large-scale properties affecting a large number of objects, based solely on the microscopic interactions between their elementary constituents. Statistical physics, precisely created to
arXiv:1610.04337v1
fatcat:7dvgbovovnf4hpelj5peux6nti