상세정보
Export to Refworks부가기능
Interdisciplinary Machine Learning Methods for Particle Physics
상세 프로파일
| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | Interdisciplinary Machine Learning Methods for Particle Physics. |
| 개인저자 | Pettee, Mariel. |
| 단체저자명 | Yale University. Physics. |
| 발행사항 | [S.l.]: Yale University., 2021. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2021. |
| 형태사항 | 181 p. |
| 기본자료 저록 | Dissertations Abstracts International 83-02B. Dissertation Abstract International |
| ISBN | 9798534651768 |
| 학위논문주기 | Thesis (Ph.D.)--Yale University, 2021. |
| 일반주기 |
Source: Dissertations Abstracts International, Volume: 83-02, Section: B.
Advisor: Demers, Sarah. |
| 이용제한사항 | This item must not be sold to any third party vendors. |
| 일반주제명 | Particle physics. Artificial intelligence. Dance. Quantum physics. Quarks. Graph representations. Sensors. Neural networks. Symmetry. Quantum field theory. |
| 언어 | 영어 |
| 바로가기 | 
: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
