We present a general framework for defining priors on model structure and sampling from the posterior using the Metropolis-Hastings algorithm. The key ideas are that structure pri...
A Bayesian framework is proposed for stereo vision where solutions to both the model parameters and the disparity map are posed in terms of predictions of latent variables, given ...
Markov chain Monte Carlo has been the standard technique for inferring the posterior distribution of genome rearrangement scenarios under a Bayesian approach. We present here a neg...
In this paper, models and algorithms are presented for transcription of pitch and timings in polyphonic music extracts, focusing on the algorithm details of the sequential Markov ...
This paper concerns the experimental assessment of tempering as a technique for improving Bayesian inference for C&RT models. Full Bayesian inference requires the computation ...