On the Stationary Distribution of Iterative Imputations

基于随机过程的表面数据填补

Surface data imputation with stochastic processes

本文提出用源自表面纹理模拟的随机过程（高斯过程）进行表面数据填补，通过整合先验知识并采用平稳与非平稳协方差结构，在真实车削轮廓数据上验证了该方法能在保持表面特征的同时有效填补缺失值。

高效贝叶斯两步程序中的不确定性传播

Efficient Uncertainty Propagation in Bayesian Two-Step Procedures

本文提出了一种高效两步方法，通过混合分布和帕累托平滑重要性采样减少计算开销，以更准确地处理贝叶斯推断中的不确定性传播问题。

经验贝叶斯关联矩阵分解

Empirical Bayes Linked Matrix Decomposition

本文提出一种经验变分贝叶斯关联矩阵分解方法，支持二维整合、自动收缩且无需调参，在低秩信号恢复、共享与特定信号分解及缺失数据插补上表现优异，并在乳腺癌多组学数据中验证有效。

A weakly informative default prior distribution for logistic and other regression models

We propose a new prior distribution for classical (nonhierarchical) logistic regression models, constructed by first scaling all nonbinary variables to have mean 0 and standard deviation 0.5, and then placing independent Student-$t$ prior distributions on the coefficients. As a default choice, we recommend the Cauchy distribution with center 0 and scale 2.5, which in the simplest setting is a longer-tailed version of the distribution attained by assuming one-half additional success and one-half additional failure in a logistic regression. Cross-validation on a corpus of datasets shows the Cauc…

仿射追踪：概率线性求解器的新范式

Affine Tracing: A New Paradigm for Probabilistic Linear Solvers

本文提出仿射追踪框架，通过自动构建概率迭代方法，实现非平稳仿射PIMs，解决概率线性求解器的不确定性量化问题。

完全条件规范在正态线性模型中使用正态逆伽玛先验的联合分布性质

Joint distribution properties of Fully Conditional Specification under the normal linear model with normal inverse-gamma priors

本文研究了在正态线性模型中使用正态逆伽玛先验的完全条件规范的收敛性，证明了在线性回归模型下联合模型与条件模型的先验规范等价性。