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04/17/2016
Regularizing Solutions to the MEG Inverse Problem Using Space-Time Separable Covariance Functions
In magnetoencephalography (MEG) the conventional approach to source reco...
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12/16/2014
Expectation propagation as a way of life: A framework for Bayesian inference on partitioned data
A common approach for Bayesian computation with big data is to partition...
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04/22/2014
Approximate Inference for Nonstationary Heteroscedastic Gaussian process Regression
This paper presents a novel approach for approximate integration over th...
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03/27/2013
Expectation Propagation for Neural Networks with Sparsity-promoting Priors
We propose a novel approach for nonlinear regression using a two-layer n...
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07/16/2012
Nested Expectation Propagation for Gaussian Process Classification with a Multinomial Probit Likelihood
We consider probabilistic multinomial probit classification using Gaussi...
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06/25/2012
Bayesian Modeling with Gaussian Processes using the GPstuff Toolbox
Gaussian processes (GP) are powerful tools for probabilistic modeling pu...
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06/22/2011