Modern Bayesian Experimental Design-Reference-Cited by-同舟云学术

Modern Bayesian Experimental Design

Published:2024-02-01 Issue:1 Volume:39 Page:
ISSN:0883-4237
Container-title:Statistical Science
language:
Short-container-title:Statist. Sci.

Author:

Rainforth Tom¹,Foster Adam²,Ivanova Desi R.³,Bickford Smith Freddie⁴

Affiliation:

1. Tom Rainforth is a Senior Researcher, Department of Statistics, University of Oxford, Oxford, UK

2. Adam Foster is a Senior Researcher, Microsoft Research AI4Science, Cambridge, UK

3. Desi R. Ivanova is a DPhil Student, University of Oxford, Oxford, UK

4. Freddie Bickford Smith is a DPhil Student, University of Oxford, Oxford, UK

Publisher

Institute of Mathematical Statistics

Reference171 articles.

1. Kingma, D. P. and Welling, M. (2014). Auto-encoding variational Bayes. In International Conference on Learning Representations.

2. Atkinson, A. C., Donev, A. N. and Tobias, R. D. (2007). Optimum Experimental Designs, with SAS. Oxford Statistical Science Series 34. Oxford Univ. Press, Oxford.

3. Chaloner, K. and Larntz, K. (1989). Optimal Bayesian design applied to logistic regression experiments. J. Statist. Plann. Inference 21 191–208.

4. Overstall, A. M. and Woods, D. C. (2017). Bayesian design of experiments using approximate coordinate exchange. Technometrics 59 458–470.

5. Kleijn, B. J. K. and van der Vaart, A. W. (2012). The Bernstein–Von-Mises theorem under misspecification. Electron. J. Stat. 6 354–381.

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