Discovering multiscale and self-similar structure with data-driven wavelets
Abstract
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.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Dec 21, 2020
- Source ID
- 10.1073/pnas.2021299118
Entities
People
- Daniel Floryan
- Michael D. Graham
Organizations
- Air Force Office of Scientific Research
- Office of Naval Research
- University of Wisconsin–Madison