Sequential analysis of simulation output is generally accepted as the most efficient way for securing representativeness of samples of collected observations. In this scenario a s...
Donald C. McNickle, Krzysztof Pawlikowski, Gregory...
Variational Bayesian Expectation-Maximization (VBEM), an approximate inference method for probabilistic models based on factorizing over latent variables and model parameters, has ...
phies are also mentioned and a common mathematical abstraction for all these inverses problems will be presented. By focusing on a simple linear forward model, first a synthetic an...
In the general classification context the recourse to the so-called Bayes decision rule requires to estimate the class conditional probability density functions. In this paper we p...
We provide a general framework for learning precise, compact, and fast representations of the Bayesian predictive distribution for a model. This framework is based on minimizing t...