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» Bayesian Inference for PCFGs via Markov Chain Monte Carlo
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UAI
2001
13 years 6 months ago
Markov Chain Monte Carlo using Tree-Based Priors on Model Structure
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...
Nicos Angelopoulos, James Cussens
CVIU
2007
154views more  CVIU 2007»
13 years 4 months ago
Bayesian stereo matching
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 ...
Li Cheng, Terry Caelli
TCBB
2010
137views more  TCBB 2010»
12 years 11 months ago
The Metropolized Partial Importance Sampling MCMC Mixes Slowly on Minimum Reversal Rearrangement Paths
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...
István Miklós, Bence Melykuti, Krist...
ICASSP
2011
IEEE
12 years 8 months ago
Point process MCMC for sequential music transcription
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 ...
Pete Bunch, Simon J. Godsill
ICML
2005
IEEE
14 years 5 months ago
Tempering for Bayesian C&RT
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 ...
Nicos Angelopoulos, James Cussens