Aki Vehtari
Title
Cited by
Cited by
Year
Bayesian data analysis
A Gelman, JB Carlin, HS Stern, DB Dunson, A Vehtari, DB Rubin
Chapman hall/CRC Press, 2013
31268*2013
Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC
A Vehtari, A Gelman, J Gabry
Statistics and computing 27 (5), 1413-1432, 2017
21272017
Understanding predictive information criteria for Bayesian models
A Gelman, J Hwang, A Vehtari
Statistics and computing 24 (6), 997-1016, 2014
13502014
One vs three years of adjuvant imatinib for operable gastrointestinal stromal tumor: a randomized trial
H Joensuu, M Eriksson, KS Hall, JT Hartmann, D Pink, J Schütte, ...
Jama 307 (12), 1265-1272, 2012
9602012
Risk of recurrence of gastrointestinal stromal tumour after surgery: an analysis of pooled population-based cohorts
H Joensuu, A Vehtari, J Riihimäki, T Nishida, SE Steigen, P Brabec, ...
The lancet oncology 13 (3), 265-274, 2012
7812012
Rao-Blackwellized particle filter for multiple target tracking
S Särkkä, A Vehtari, J Lampinen
Information Fusion 8 (1), 2-15, 2007
3282007
Bayesian approach for neural networks—review and case studies
J Lampinen, A Vehtari
Neural networks 14 (3), 257-274, 2001
3222001
loo: Efficient leave-one-out cross-validation and WAIC for Bayesian models
A Vehtari, J Gabry, Y Yao, A Gelman
R package version 2 (0), 1003, 2018
3192018
Visualization in Bayesian workflow
J Gabry, D Simpson, A Vehtari, M Betancourt, A Gelman
Journal of the Royal Statistical Society Series A, 2017
3052017
A survey of Bayesian predictive methods for model assessment, selection and comparison
A Vehtari, J Ojanen
Statistics Surveys 6, 142-228, 2012
2862012
R-squared for Bayesian regression models
A Gelman, B Goodrich, J Gabry, A Vehtari
The American Statistician, 2019
2752019
GPstuff: Bayesian modeling with Gaussian processes
J Vanhatalo, J Riihimäki, J Hartikainen, P Jylänki, V Tolvanen, A Vehtari
Journal of Machine Learning Research 14 (Apr), 1175-1179, 2013
2722013
Using stacking to average Bayesian predictive distributions
Y Yao, A Vehtari, D Simpson, A Gelman
Bayesian Analysis 13 (3), 917-1003, 2018
2282018
Comparison of Bayesian predictive methods for model selection
J Piironen, A Vehtari
Statistics and Computing 27 (3), 711-735, 2017
2212017
Rank-normalization, folding, and localization: An improved for assessing convergence of MCMC
A Vehtari, A Gelman, D Simpson, B Carpenter, PC Bürkner
arXiv preprint arXiv:1903.08008, 2019
2102019
Sparsity information and regularization in the horseshoe and other shrinkage priors
J Piironen, A Vehtari
Electronic Journal of Statistics 11 (2), 5018-5051, 2017
2012017
Bayesian model assessment and comparison using cross-validation predictive densities
A Vehtari, J Lampinen
Neural computation 14 (10), 2439-2468, 2002
1952002
Gaussian processes with monotonicity information
J Riihimäki, A Vehtari
Proceedings of the thirteenth international conference on artificial …, 2010
1672010
Pareto smoothed importance sampling
A Vehtari, D Simpson, A Gelman, Y Yao, J Gabry
arXiv preprint arXiv:1507.02646, 2015
1512015
Robust Gaussian Process Regression with a Student-t Likelihood.
P Jylänki, J Vanhatalo, A Vehtari
Journal of Machine Learning Research 12 (11), 2011
1502011
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Articles 1–20