Bayesian updating is reframed as an optimization problem without inherent uncertainty quantification, and a PAC-style calibration step is proposed to give predictive intervals frequentist coverage.
Bayesian neural networks via mcmc: a python-based tutorial
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
stat.ML 1years
2025 1verdicts
CONDITIONAL 1roles
background 1polarities
background 1representative citing papers
citing papers explorer
-
Position: There Is No Free Bayesian Uncertainty Quantification
Bayesian updating is reframed as an optimization problem without inherent uncertainty quantification, and a PAC-style calibration step is proposed to give predictive intervals frequentist coverage.