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Factored expectation propagation for input-output FHMM models in systems biology
input output factored hidden Markov models approximate inference variational inference expectation propagation systems biology microarray data
2013/6/14
We consider the problem of joint modelling of metabolic signals and gene expression in systems biology applications. We propose an approach based on input-output factorial hidden Markov models and pro...
Expectation Propagation for Neural Networks with Sparsity-promoting Priors
expectation propagation neural network multilayer perceptron linear model sparse prior automatic relevance determination
2013/4/28
We propose a novel approach for nonlinear regression using a two-layer neural network (NN) model structure with sparsity-favoring hierarchical priors on the network weights. We present an expectation ...
Nested Expectation Propagation for Gaussian Process Classification with a Multinomial Probit Likelihood
Gaussian process multiclass classification multinomial probit approximate inference expectation propagation
2012/9/19
We consider probabilistic multinomial probit classification using Gaussian process (GP) priors. The challenges with the multiclass GP classification are the integration over the non-Gaussian posterior...
Expectation Propagation in Gaussian Process Dynamical Systems
Expectation Propagation Gaussian Process Dynamical Systems
2012/9/19
Rich and complex time-series data, such as those generated from engineer-ing systems, financial markets, videos or neural recordings, are now a common feature of modern data analysis. Explaining the p...
Fast Convergent Algorithms for Expectation Propagation Approximate Bayesian Inference
Machine Learning (stat.ML)
2010/12/17
We propose a novel algorithm to solve the expectation propagation relaxation of Bayesian inference for continuous-variable graphical models. In contrast to most previous algorithms, our method is prov...