Prediction and optimization of epoxy adhesive strength from a small dataset through active learning
- ジャーナル論文
- 著者
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Lambard, Guillaume (author) (この著者で検索)
;
Naito, Masanobu (author) (この著者で検索)
;
Samitsu, Sadaki (author) (この著者で検索)
;
Pruksawan, Sirawit (author) (この著者で検索)
https://orcid.org/0000-0002-9380-1872
(unauthenticated)
;
Sodeyama, Keitaro (author) (この著者で検索)
- キーワード
- active learning, Machine learning, adhesive
- 刊行年月日
- 2019-12-31
- 更新時刻
- 2024-01-05 22:11:50 +0900
A straightforward gradient-based approach for designing superconductors with high critical temperature: exploiting domain knowledge via adaptive constraints
- ジャーナル論文
- 著者
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;Akihiro Fujii (author) (この著者で検索)Anh Khoa Augustin Lu (author) (この著者で検索)National Institute for Materials Science
;
;Koji Shimizu (author) (この著者で検索)Satoshi Watanabe (author) (この著者で検索)
https://orcid.org/0000-0002-8069-6938
(unauthenticated)
National Institute for Materials Science
- キーワード
- Gradient-based optimization, Superconductor, Domain knowledge integration, Materials discovery, Critical temperature, Machine learning
- 刊行年月日
- 2025-10-29
- 更新時刻
- 2026-05-18 14:53:14 +0900