Sparse modeling based Bayesian optimization for experimental design
Efficiently optimizing high-dimensional synthesis parameters via Bayesian optimization (BO) is a challenge in recent materials exploration. This study introduces a sparse modeling-based BO method using the maximum partial dependence effect (MPDE).
Authors
- un-Beom Lee
- Ryuji Masui
- Ryo Nakayama (ORCID: https://orcid.org/0000-0001-6284-9884)
- Taro Hitosugi (ORCID: https://orcid.org/0000-0002-7795-0683)
Institutions
- The University of Tokyo (JP)
Publication Details
- Journal
- Materials Advances
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1039/d5ma00346f
- Primary Topic
- Advanced Battery Technologies Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Ministry of Education, Culture, Sports, Science and Technology
- Japan Society for the Promotion of Science
- Japan Science and Technology Agency
- Core Research for Evolutional Science and Technology
- JST-Mirai Program