—We consider the Bayesian inference of a random Gaussian vector in a linear model with a random Gaussian matrix. We review two approaches to finding the MAP estimator for this m...
We present learning and inference algorithms for a versatile class of partially observed vector autoregressive (VAR) models for multivariate time-series data. VAR models can captu...
Background: The application of high throughput approaches to the identification of protein interactions has offered for the first time a glimpse of the global interactome of some ...
Maria Persico, Arnaud Ceol, Caius Gavrila, Robert ...
Software behavioral models have proven useful for design, validation, verification, and maintenance. However, existing approaches for deriving such models sometimes overgeneraliz...
Ivo Krka, Yuriy Brun, Daniel Popescu, Joshua Garci...
Functional mixed-effects models are very useful in analyzing functional data. A general functional mixed-effects model that inherits the flexibility of linear mixed-effects model...