Supervised cadre models for subpopulation-based learning

Authors
New, Alexander
ORCID
Loading...
Thumbnail Image
Other Contributors
Bennett, Kristin P.
Mitchell, John E.
Xu, Yangyang
Ji, Qiang, 1963-
Issue Date
2019-08
Keywords
Mathematics
Degree
PhD
Terms of Use
This electronic version is a licensed copy owned by Rensselaer Polytechnic Institute, Troy, NY. Copyright of original work retained by author.
Full Citation
Abstract
We consider four primary case studies. The first applies scalar regression to materials-by-design. In it, the SCM provides state-of-the-art prediction of polymer glass transition temperature. The method identifies cadres of polymers that respond differently to structural perturbations, thus providing design insight for targeting or avoiding specific transition temperature ranges. It identifies chemically meaningful polymer subpopulations.
Description
August 2019
School of Science
Department
Dept. of Mathematical Sciences
Publisher
Rensselaer Polytechnic Institute, Troy, NY
Relationships
Rensselaer Theses and Dissertations Online Collection
Access
Restricted to current Rensselaer faculty, staff and students. Access inquiries may be directed to the Rensselaer Libraries.