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A. Gelman, A. Vehtari, D. Simpson, C. Margossian, B. Carpenter, Y. Yao, L. Kennedy, J. Gabry, P. Bürkner, and M. Modrák. arXiv preprint, (2020)

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Comparison of Bayesian predictive methods for model selection.J. Piironen, and A. Vehtari. Statistics and Computing, 27 (3): 711-735 (2017)Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC.A. Vehtari, A. Gelman, and J. Gabry. Statistics and Computing, 27 (5): 1413-1432 (2017)Expectation propagation for neural networks with sparsity-promoting priors.P. Jylänki, A. Nummenmaa, and A. Vehtari. J. Mach. Learn. Res., 15 (1): 1849-1901 (2014)Robust Gaussian Process Regression with a Student-t Likelihood.P. Jylänki, J. Vanhatalo, and A. Vehtari. J. Mach. Learn. Res., (2011)Bayesian Model Assessment and Comparison Using Cross-Validation Predictive Densities.A. Vehtari, and J. Lampinen. Neural Computation, 14 (10): 2439-2468 (2002)Bayesian approach for neural networks--review and case studies.J. Lampinen, and A. Vehtari. Neural Networks, 14 (3): 257-274 (2001)Correcting boundary over-Exploration Deficiencies in Bayesian Optimization with Virtual derivative Sign observations.E. Siivola, A. Vehtari, J. Vanhatalo, J. Gonzalez, and M. Andersen. MLSP, page 1-6. IEEE, (2018)Active Learning for Decision-Making from Imbalanced Observational Data.I. Sundin, P. Schulam, E. Siivola, A. Vehtari, S. Saria, and S. Kaski. ICML, volume 97 of Proceedings of Machine Learning Research, page 6046-6055. PMLR, (2019)Graphical test for discrete uniformity and its applications in goodness-of-fit evaluation and multiple sample comparisonT. Säilynoja, P. Bürkner, and A. Vehtari. Statistics and Computing, (2022)GPstuff: Bayesian modeling with Gaussian processes.J. Vanhatalo, J. Riihimäki, J. Hartikainen, P. Jylänki, V. Tolvanen, and A. Vehtari. J. Mach. Learn. Res., 14 (1): 1175-1179 (2013)

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copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Bayesian workflow

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Bayesian workflow