54 citations · 78 across the 2 of their papers we have counts for
3 papers
Bayesian leave-one-out cross-validation approximations for Gaussian latent variable models
Aki Vehtari, Tommi Mononen, Ville Tolvanen +2
The future predictive performance of a Bayesian model can be estimated using Bayesian cross-validation. In this article, we consider Gaussian latent variable models where the integ…
Approximate Inference for Nonstationary Heteroscedastic Gaussian process Regression
Ville Tolvanen, Pasi Jylänki, Aki Vehtari
This paper presents a novel approach for approximate integration over the uncertainty of noise and signal variances in Gaussian process (GP) regression. Our efficient and straightf…
Bayesian Modeling with Gaussian Processes using the GPstuff Toolbox
Jarno Vanhatalo, Jaakko Riihimäki, Jouni Hartikainen +3
Gaussian processes (GP) are powerful tools for probabilistic modeling purposes. They can be used to define prior distributions over latent functions in hierarchical Bayesian models…