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Discussion on Bayesian Cluster Analysis: Point Estimation and Credible Balls by Sara Wade and Zoubin Ghahramani
William Weimin Yoo
I begin my discussion by giving an overview of the main results. Then I proceed to touch upon issues about whether the credible ball constructed can be interpreted as a confidence…
Bayesian cluster analysis: Point estimation and credible balls
Sara Wade, Zoubin Ghahramani
Clustering is widely studied in statistics and machine learning, with applications in a variety of fields. As opposed to classical algorithms which return a single clustering solut…
Gaussian Process Volatility Model
Yue Wu, Jose Miguel Hernandez Lobato, Zoubin Ghahramani
The accurate prediction of time-changing variances is an important task in the modeling of financial data. Standard econometric models are often limited as they assume rigid functi…
Dynamic Covariance Models for Multivariate Financial Time Series
Yue Wu, José Miguel Hernández-Lobato, Zoubin Ghahramani
The accurate prediction of time-changing covariances is an important problem in the modeling of multivariate financial data. However, some of the most popular models suffer from a)…
Gaussian Process Vine Copulas for Multivariate Dependence
David Lopez-Paz, José Miguel Hernández-Lobato, Zoubin Ghahramani
Copulas allow to learn marginal distributions separately from the multivariate dependence structure (copula) that links them together into a density function. Vine factorizations e…
Bayesian Inference for Gaussian Mixed Graph Models
Ricardo Silva, Zoubin Ghahramani
We introduce priors and algorithms to perform Bayesian inference in Gaussian models defined by acyclic directed mixed graphs. Such a class of graphs, composed of directed and bi-di…