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Geometric Bayes
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| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | Geometric Bayes. |
| 개인저자 | Holbrook, Andrew J. |
| 단체저자명 | University of California, Irvine. Statistics - Ph.D.. |
| 발행사항 | [S.l.]: University of California, Irvine., 2018. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2018. |
| 형태사항 | 207 p. |
| 기본자료 저록 | Dissertation Abstracts International 80-01B(E). Dissertation Abstract International |
| ISBN | 9780438304321 |
| 학위논문주기 | Thesis (Ph.D.)--University of California, Irvine, 2018. |
| 일반주기 |
Source: Dissertation Abstracts International, Volume: 80-01(E), Section: B.
Adviser: Babak Shahbaba. |
| 요약 | This dissertation is an investigation into the intersections between differential geometry and Bayesian analysis. The former is the mathematical discipline that underlies our understanding of the spatial structure of the universe |
| 요약 | A major component of this work is the development and application of probabilistic models defined over smooth manifolds: dependencies between time series are modeled using the manifold of Hermitian positive definite matrices |
| 요약 | This dissertation is ordered as follows. In Chapter 1, the general setting is introduced along with the rudiments of Riemannian geometry. In Chapter 2, the geodesic Lagrangian Monte Carlo algorithm is presented and used for Bayesian inference ov |
| 일반주제명 | Statistics. Applied mathematics. Computer science. |
| 언어 | 영어 |
| 바로가기 | 
: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
