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
From Random Networks to AI-Driven Glass Design
- プレゼンテーション
- 著者
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N. M. Anoop Krishnan (author) (この著者で検索)Indian Institute of Technology Delhi Department of Civil Engineering
- キーワード
- Machine learning, AI-Driven Glass Design
- 刊行年月日
- 更新時刻
- 2025-09-25 16:30:42 +0900