Generative broad Bayesian (GBB) imputer for missing data imputation with uncertainty quantification-Reference-Cited by-同舟云学术

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Generative broad Bayesian (GBB) imputer for missing data imputation with uncertainty quantification

Published:2024-10 Issue: Volume:301 Page:112272
ISSN:0950-7051
Container-title:Knowledge-Based Systems
language:en
Short-container-title:Knowledge-Based Systems

Author:

Kuok Sin-Chi^ORCID,Yuen Ka-Veng^ORCID,Dodwell Tim,Girolami Mark

Publisher

Elsevier BV

Reference54 articles.

1. Where to drill next? A dual-weighted approach to adaptive optimal design of groundwater surveys;Lykkegaard;Adv. Water. Resour.,2022

2. Topic analysis and forecasting for science, technology and innovation: methodology with a case study focusing on big data research;Zhang;Technol. Forecast. Soc. Change,2016

3. Efficient Bayesian sensor placement algorithm for structural identification: a general approach for multi-type sensory systems;Yuen;Earthq. Eng. Struct. Dyn.,2015

4. Statistical Analysis With Missing Data;Little,2019

5. Missing Data Analysis in Practice;Raghunathan,2015

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