Using Bayesian parameter estimation to learn more from data without black boxes

被引：0

作者：

Rachel C. Kurchin

机构：

[1] Carnegie Mellon University,

[2] Materials Science and Engineering Department,undefined

来源：

Nature Reviews Physics | 2024年 / 6卷

关键词：

D O I：

暂无

中图分类号：

学科分类号：

摘要：

In an age of expensive experiments and hype around new data-driven methods, researchers understandably want to ensure they are gleaning as much insight from their data as possible. Rachel C. Kurchin argues that there is still plenty to be learned from older approaches without turning to black boxes.

引用

页码：152 / 154

页数：2

共 50 条

[1] Using Bayesian parameter estimation to learn more from data without black boxes
Kurchin, Rachel C.
NATURE REVIEWS PHYSICS, 2024, 6 (03) : 160 - 161
[2] SHOULD BLACK-BOXES CONTAIN MORE DATA
TENCH, W
NEW SCIENTIST, 1985, 107 (1470) : 21 - 22
[3] Copula parameter estimation using Bayesian inference for pipe data analysis
Atique, Farzana
Attoh-Okine, Nii
CANADIAN JOURNAL OF CIVIL ENGINEERING, 2018, 45 (01) : 61 - 70
[4] Parameter estimation for Bayesian classification of multispectral data
Mohamed, RM
Farag, AA
KNOWLEDGE-BASED INTELLIGENT INFORMATION AND ENGINEERING SYSTEMS, PT 1, PROCEEDINGS, 2003, 2773 : 346 - 355
[5] ThetaMater: Bayesian estimation of population size parameter θ from genomic data
Adams, Richard H.
Schield, Drew R.
Card, Daren C.
Corbin, Andrew
Castoe, Todd A.
BIOINFORMATICS, 2018, 34 (06) : 1072 - 1073
[6] Bayesian Approach to Learn Bayesian Networks Using Data and Constraints
Gao Xiao-guang
Yang Yu
Guo Zhi-gao
Chen Da-qing
2016 23RD INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR), 2016, : 3667 - 3672
[7] Parameter Estimation of Reliability Growth Model with Incomplete Data Using Bayesian Method
Park, Cheongeon
Lim, Jisung
Lee, Sangchul
JOURNAL OF THE KOREAN SOCIETY FOR AERONAUTICAL AND SPACE SCIENCES, 2019, 47 (10) : 747 - 752
[8] Redefining the incidents to learn from: Safety science insights acquired on the journey from black boxes to Flight Data Monitoring
Walker, Guy
SAFETY SCIENCE, 2017, 99 : 14 - 22
[9] Improved Placental Parameter Estimation Using Data-Driven Bayesian Modelling
Flouri, Dimitra
Owen, David
Aughwane, Rosalind
Mufti, Nada
Sokolska, Magdalena
Atkinson, David
Kendall, Giles
Bainbridge, Alan
Vercauteren, Tom
David, Anna L.
Ourselin, Sebastien
Melbourne, Andrew
MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION - MICCAI 2019, PT III, 2019, 11766 : 609 - 616
[10] Exploring the Bayesian parameter estimation of binary black holes with LISA
Marsat, Sylvain
Baker, John G.
Dal Canton, Tito
PHYSICAL REVIEW D, 2021, 103 (08)

← 1 2 3 4 5 →