This paper proposes a new framework of speech synthesis based on the Bayesian approach. The Bayesian method is a statistical technique for estimating reliable predictive distribut...
Kei Hashimoto, Heiga Zen, Yoshihiko Nankaku, Takas...
Bayesian learning in undirected graphical models--computing posterior distributions over parameters and predictive quantities-is exceptionally difficult. We conjecture that for ge...
— This work deals with a group of mobile sensors sampling a spatiotemporal random field whose mean is unknown and covariance is known up to a scaling parameter. The Bayesian pos...
We present a framework for efficient, accurate approximate Bayesian inference in generalized linear models (GLMs), based on the expectation propagation (EP) technique. The paramete...
Matthias Seeger, Sebastian Gerwinn, Matthias Bethg...
We propose a Bayesian extension to the ad-hoc Language Model. Many smoothed estimators used for the multinomial query model in ad-hoc Language Models (including Laplace and Bayes-...
Hugo Zaragoza, Djoerd Hiemstra, Michael E. Tipping