WebA nonparametric Bayesian extension of Factor Analysis (FA) is proposed where observed data $\mathbf{Y}$ is modeled as a linear superposition, $\mathbf{G}$, of a potentially … WebWe focus on sparse modeling of high-dimensional covariance matrices using Bayesian latent factor models. We propose a multiplicative gamma process shrinkage prior on the …

[2101.04491] Bayesian inference in high-dimensional models

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CVPR2024_玖138的博客-CSDN博客

WebMost of previous works and applications of Bayesian factor model have assumed the normal likelihood regardless of its validity. We propose a Bayesian factor model for heavy … Web10. aug 2002 · Bayesian approaches have modelled the sparsity of factor loadings by using sparsity-inducing priors such as a "spike and slab prior" West (2003). Markov chain Monte Carlo (MCMC), which... WebThe model's utility for modeling gene expression data is investigated using randomly generated data sets based on a known sparse connectivity matrix for E. Coli, and on three biological data sets of increasing complexity. Publication: arXiv e-prints Pub Date: November 2010 DOI: 10.48550/arXiv.1011.6293 arXiv: arXiv:1011.6293 Bibcode: the rabge.ie