| Bayesian data analysis, 3rd edition A Gelman, JB Carlin, HS Stern, DB Dunson, A Vehtari, DB Rubin Chapman and Hall/CRC, 2013 | 44396* | 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 | 6676 | 2017 |
| Understanding predictive information criteria for Bayesian models A Gelman, J Hwang, A Vehtari Statistics and computing 24 (6), 997-1016, 2014 | 2748 | 2014 |
| 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 | 2277* | 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 | 1308 | 2012 |
| Visualization in Bayesian workflow J Gabry, D Simpson, A Vehtari, M Betancourt, A Gelman Journal of the Royal Statistical Society Series A, 2017 | 1302 | 2017 |
| Regression and other stories A Gelman, J Hill, A Vehtari Cambridge University Press, 2021 | 1190* | 2021 |
| 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 | 1186 | 2012 |
| loo: Efficient leave-one-out cross-validation and WAIC for Bayesian models A Vehtari, J Gabry, M Magnusson, Y Yao, PC Bürkner, T Paananen, ... (No Title), 2015 | 1080* | 2015 |
| R-squared for Bayesian regression models A Gelman, B Goodrich, J Gabry, A Vehtari The American Statistician 73 (3), 307-309, 2019 | 1065 | 2019 |
| Using stacking to average Bayesian predictive distributions Y Yao, A Vehtari, D Simpson, A Gelman Bayesian Analysis 13 (3), 917-1003, 2018 | 787* | 2018 |
| Sparsity information and regularization in the horseshoe and other shrinkage priors J Piironen, A Vehtari Electronic Journal of Statistics 11 (2), 5018-5051, 2017 | 626 | 2017 |
| Bayesian workflow A Gelman, A Vehtari, D Simpson, CC Margossian, B Carpenter, Y Yao, ... arXiv preprint arXiv:2011.01808, 2020 | 612* | 2020 |
| Bayesian approach for neural networks—review and case studies J Lampinen, A Vehtari Neural networks 14 (3), 257-274, 2001 | 555 | 2001 |
| Pareto smoothed importance sampling A Vehtari, D Simpson, A Gelman, Y Yao, J Gabry Journal of Machine Learning Research 25 (72), 1-58, 2024 | 524 | 2024 |
| A survey of Bayesian predictive methods for model assessment, selection and comparison A Vehtari, J Ojanen Statistics Surveys 6, 142-228, 2012 | 483 | 2012 |
| Comparison of Bayesian predictive methods for model selection J Piironen, A Vehtari Statistics and Computing 27 (3), 711-735, 2017 | 454 | 2017 |
| Rao-Blackwellized particle filter for multiple target tracking S Särkkä, A Vehtari, J Lampinen Information Fusion 8 (1), 2-15, 2007 | 405 | 2007 |
| 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 | 384* | 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 | 368 | 2018 |
Andrew GelmanProfessor of Statistics and Political Science, Columbia UniversityVerified email at stat.columbia.edu
