Bayesian Data Analysis

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On the Equivalence between Kernel Quadrature Rules and Random Feature Expansions (2015, background): “ional integrals is one of the core computational tasks in many areas of machine learning, signal processing and more generally applied mathematics, in particular in the context of Bayesian inference (Gelman, 2004), or the study of complex systems (Robert and Casella, 2005). In this paper, we focus o”
Hyperspectral Pansharpening: A Review (2015, background): “Spatial information provided by PCA is better since the main information of HS image (where the spatial information is contained) is replaced by the high spatial information contained in the PAN image.”
A multivariate empirical Bayes statistic for replicated microarray time course data (2006, methodology): “Hero and Fleury (2002) and Fleury et al.”
Bayesian Spatial Modeling of Extreme Precipitation Return Levels (2007, methodology): “For background on MCMC methods, see Robert and Casella (1999), and for a reference on Bayesian inference via MCMC, see Gelman et al. (2003). For both the”
The statistical finite element method (statFEM) for coherent synthesis of observation data and model predictions (2019, unknown): “, the books [6–10] for an introduction to Bayesian statistics and data analysis.”