Title: Discovering multiscale and self-similar structure with data-driven wavelets
Abstract: Significance Multiscale structure is all around us: in biological tissues, active matter, oceans, networks, and images. Identifying the multiscale features of these systems is crucial to our understanding and control of them. We introduce a method that rationally extracts localized multiscale features from data, which may be thought of as the building blocks of the underlying phenomena.