Path-Following Methods for Maximum a Posteriori Estimators in Bayesian Hierarchical Models: How Estimates Depend on Hyperparameters-Reference-Cited by-同舟云学术

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Path-Following Methods for Maximum a Posteriori Estimators in Bayesian Hierarchical Models: How Estimates Depend on Hyperparameters

Published:2024-07-01 Issue:3 Volume:34 Page:2201-2230
ISSN:1052-6234
Container-title:SIAM Journal on Optimization
language:en
Short-container-title:SIAM J. Optim.

Author:

Si Zilai¹,Liu Yucong²,Strang Alexander³

Affiliation:

1. Department of Industrial Engineering & Management Sciences, Northwestern University, Evanston, IL 60208 USA.

2. School of Mathematics, Georgia Institute of Technology, Atlanta, GA 30332 USA.

3. Department of Statistics, The University of California, Berkeley, CA 94720 USA.

Publisher

Society for Industrial & Applied Mathematics (SIAM)

Reference34 articles.

1. A Variational Inference Approach to Inverse Problems with Gamma Hyperpriors

2. E. L. Allgower and K. Georg, Continuation and Path Following, Acta Numer., Cambridge University Press, Cambridge, 1993, pp. 1–64.

3. Conditionally Gaussian Hypermodels for Cerebral Source Localization

4. A hierarchical Krylov–Bayes iterative inverse solver for MEG with physiological preconditioning

5. Brain Activity Mapping from MEG Data via a Hierarchical Bayesian Algorithm with Automatic Depth Weighting

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