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.

翻译：共轭梯度是一种求解大规模稀疏线性系统的高效算法，已被用于加速许多大规模问题中的贝叶斯分析计算。本文讨论了共轭梯度在贝叶斯计算中的应用，重点关注稀疏回归和空间分析。为促进其在更广泛问题中的潜在应用，本文提供了关于共轭梯度的自包含介绍。