We propose a more efficient version of the slice sampler for Dirichlet process mixture models described by Walker (2007). This sampler allows the fitting of infinite mixture mod...
Many probabilistic models introduce strong dependencies between variables using a latent multivariate Gaussian distribution or a Gaussian process. We present a new Markov chain Mo...
Iain Murray, Ryan Prescott Adams, David J. C. MacK...
This paper describes an efficient sampler for synchronous grammar induction under a nonparametric Bayesian prior. Inspired by ideas from slice sampling, our sampler is able to dra...
Real-valued random hidden variables can be useful for modelling latent structure that explains correlations among observed variables. I propose a simple unit that adds zero-mean G...
Modeling the dynamics of heart and lung tissue is challenging because the tissue deforms between data acquisitions. To reconstruct complete volumes, sample data captured at differ...
Manfred Georg, Richard Souvenir, Andrew Hope, Robe...