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Aki Vehtari
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Jahr
Bayesian data analysis, 3rd edition
A Gelman, JB Carlin, HS Stern, DB Dunson, A Vehtari, DB Rubin
Chapman and Hall/CRC, 2013
40436*2013
Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC
A Vehtari, A Gelman, J Gabry
Statistics and computing 27, 1413-1432, 2017
52722017
Understanding predictive information criteria for Bayesian models
A Gelman, J Hwang, A Vehtari
Statistics and computing 24, 997-1016, 2014
23742014
Rank-normalization, folding, and localization: An improved for assessing convergence of MCMC
A Vehtari, A Gelman, D Simpson, B Carpenter, PC Bürkner
Bayesian analysis 16 (2), 667-718, 2021
1464*2021
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
11952012
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
11002012
Visualization in Bayesian workflow
J Gabry, D Simpson, A Vehtari, M Betancourt, A Gelman
Journal of the Royal Statistical Society Series A, 2017
9892017
Regression and other stories
A Gelman, J Hill, A Vehtari
Cambridge University Press, 2021
877*2021
loo: Efficient leave-one-out cross-validation and WAIC for Bayesian models
A Vehtari, J Gabry, M Magnusson, Y Yao, PC Bürkner, T Paananen, ...
CRAN: Contributed Packages, 2015
849*2015
R-squared for Bayesian regression models
A Gelman, B Goodrich, J Gabry, A Vehtari
The American Statistician 73 (3), 307-309, 2019
8402019
Using stacking to average Bayesian predictive distributions
Y Yao, A Vehtari, D Simpson, A Gelman
Bayesian Analysis 13 (3), 917-1003, 2018
6422018
Sparsity information and regularization in the horseshoe and other shrinkage priors
J Piironen, A Vehtari
Electronic Journal of Statistics 11 (2), 5018-5051, 2017
4942017
Bayesian approach for neural networks—review and case studies
J Lampinen, A Vehtari
Neural networks 14 (3), 257-274, 2001
4942001
A survey of Bayesian predictive methods for model assessment, selection and comparison
A Vehtari, J Ojanen
Statistics Surveys 6, 142-228, 2012
4412012
Bayesian workflow
A Gelman, A Vehtari, D Simpson, CC Margossian, B Carpenter, Y Yao, ...
arXiv preprint arXiv:2011.01808, 2020
413*2020
Rao-Blackwellized particle filter for multiple target tracking
S Särkkä, A Vehtari, J Lampinen
Information Fusion 8 (1), 2-15, 2007
3982007
Comparison of Bayesian predictive methods for model selection
J Piironen, A Vehtari
Statistics and Computing 27, 711-735, 2017
3892017
Pareto smoothed importance sampling
A Vehtari, D Simpson, A Gelman, Y Yao, J Gabry
Journal of Machine Learning Research 25 (72), 1-58, 2024
383*2024
GPstuff: Bayesian modeling with Gaussian processes
J Vanhatalo, J Riihimäki, J Hartikainen, P Jylänki, V Tolvanen, A Vehtari
Journal of Machine Learning Research 14, 1175-1179, 2013
362*2013
Validating Bayesian inference algorithms with simulation-based calibration
S Talts, M Betancourt, D Simpson, A Vehtari, A Gelman
arXiv preprint arXiv:1804.06788, 2018
2682018
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