Upon engineering a Bayesian network for the early detection of Classical Swine Fever in pigs, we found that the commonly used approach of separately modelling the relevant observab...
Linda C. van der Gaag, Janneke H. Bolt, Willie Loe...
This paper presents Bayesian edge inference (BEI), a
single-frame super-resolution method explicitly grounded in
Bayesian inference that addresses issues common to existing
meth...
Bryan S. Morse, Dan Ventura, Kevin D. Seppi, Neil ...
In many signal processing problems, it may be fruitful to represent the signal under study in a redundant linear decomposition called a frame. If a probabilistic approach is adopt...
We present an analysis of concentration-of-expectation phenomena in layered Bayesian networks that use generalized linear models as the local conditional probabilities. This frame...
-- We characterize the best achievable performance of lossy compression algorithms operating on arbitrary random sources, and with respect to general distortion measures. Direct an...