Mathematics, Methods, and Models for Data-Driven Rheology
While data-driven tools and techniques have revolutionized much of the scientific and engineering landscape, they have yet to make a substantial impact in the field of rheology. Rheological data sets are at once too scarce and too diverse to enable traditional machine learning approaches -- their sc...
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Format: | Thesis |
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Massachusetts Institute of Technology
2023
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Online Access: | https://hdl.handle.net/1721.1/153047 https://orcid.org/0000-0002-1251-5461 |