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Applications of Conjugate Gradient in Bayesian computation by Zhang, Lu is a scholarly article available to read on EtoBox.

What is Applications of Conjugate Gradient in Bayesian computation about?

Conjugate gradient is an efficient algorithm for solving large sparse linear systems. It has been utilized to accelerate the computation in Bayesian analysis for many large-scale problems. This article discusses the applications of conjugate gradient in Bayesian computation, with a focus on sparse regression and spatial analysis. A self-contained introduction of conjugate gradient is provided to facilitate potential applications in a broader range of problems.

Author

Zhang, Lu

Published

2023

Language

EN