mlsanityData to 7 Oct 2026

The prior can generally only be understood in the context of the likelihood

arXiv 1708.07487 ↗First posted 24 Aug 2017stat.MEcited by 18

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Abstract (arXiv)

A key sticking point of Bayesian analysis is the choice of prior distribution, and there is a vast literature on potential defaults including uniform priors, Jeffreys' priors, reference priors, maximum entropy priors, and weakly informative priors. These methods, however, often manifest a key conceptual tension in prior modeling: a model encoding true prior information should be chosen without reference to the model of the measurement process, but almost all common prior modeling techniques are implicitly motivated by a reference likelihood. In this paper we resolve this apparent paradox by placing the choice of prior into the context of the entire Bayesian analysis, from inference to prediction to model evaluation.

Key facts. Cited by 18 papers in the map (data through 7 Oct 2026). First posted on arXiv 24 Aug 2017.

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Citing papers per year: 2021: 3; 2022: 4; 2023: 2; 2024: 6; 2025: 2; 2026: 1.

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  1. 2021Priors in Bayesian Deep Learning: A Reviewcited by 101
  2. 2022LMPriors: Pre-Trained Language Models as Task-Specific Priorscited by 56
  3. 2022The worst of both worlds: A comparative analysis of errors in learning from data in psychology and machine learningcited by 17
  4. 2022A Bayesian Bradley-Terry model to compare multiple ML algorithms on multiple data setscited by 9
  5. 2021Ensemble Inference Methods for Models With Noisy and Expensive Likelihoodscited by 8
  6. 2022On the detrimental effect of invariances in the likelihood for variational inferencecited by 8
  7. 2024Bayesian Neural Networks with Domain Knowledge Priorscited by 8
  8. 2024Hyperparameter Optimization for Randomized Algorithms: A Case Study on Random Featurescited by 7
  9. 2024Had enough of experts? Quantitative knowledge retrieval from large language modelscited by 4
  10. 2024Graph Structure Learning with Interpretable Bayesian Neural Networkscited by 4
  11. 2025Posterior SBC: Simulation-Based Calibration Checking Conditional on Datacited by 3
  12. 2021Informative Bayesian model selection for RR Lyrae star classifierscited by 1
6 more
  1. 2023Simulation-Based Prior Knowledge Elicitation for Parametric Bayesian Modelscited by 1
  2. 2023Probabilistic load forecasting with Reservoir Computingcited by 1
  3. 2024Preferential Normalizing Flowscited by 1
  4. 2024Expert-elicitation method for non-parametric joint priors using normalizing flowscited by 1
  5. 2025Bayesian Event-Based Model for Disease Subtype and Stage Inferencecited by 1
  6. 2026Rethinking Likelihood distributions: Student's t Likelihood Boosts Bayesian Neural Network Performancecited by 0