Discussion of Big Bayes Stories and BayesBag
Not on the map. Why?
Abstract (arXiv)
I congratulate all the authors for their insightful papers with wide-ranging contributions. The articles demonstrate the power and elegance of the Bayesian inference paradigm. In particular, it allows to incorporate prior knowledge as well as hierarchical model building in a convincing way. Regarding the latter, the contribution by Raftery, Alkema and German is a very fascinating piece, as it addresses a set of problems of great public interest and presents predictions for the world populations and other interesting quantities with uncertainty regions. Their approach is based on a hierarchical model, taking various characteristics into account (e.g., fertility projections). It would have been very difficult to come up with a "better" solution which would be as clear in terms of interpretation (in contrast to a "black-box machine") and which would provide (model-based) uncertainties for the predictions into the future.
Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). First posted on arXiv 20 May 2014.
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Citing papers per year: 2021: 1; 2022: 1; 2023: 2; 2024: 1; 2025: 1.
6 papers.
- 2021Model-based metrics: Sample-efficient estimates of predictive model subpopulation performancecited by 7
- 2023Uncertainty Quantification and Propagation in Surrogate-based Bayesian Inferencecited by 4
- 2022A Probabilistic Framework for Mutation Testing in Deep Neural Networkscited by 3
- 2024Stabilizing black-box model selection with the inflated argmaxcited by 3
- 2023Reproducible Parameter Inference Using Bagged Posteriorscited by 2
- 2025Variational bagging: a robust approach for Bayesian uncertainty quantificationcited by 0
- 2025Variational bagging: a robust approach for Bayesian uncertainty quantification25 Nov 2025
- 2024Stabilizing black-box model selection with the inflated argmax23 Oct 2024
- 2023Uncertainty Quantification and Propagation in Surrogate-based Bayesian Inference8 Dec 2023
- 2023Reproducible Parameter Inference Using Bagged Posteriors3 Nov 2023
- 2022A Probabilistic Framework for Mutation Testing in Deep Neural Networks11 Aug 2022
- 2021Model-based metrics: Sample-efficient estimates of predictive model subpopulation performance25 Apr 2021