2 papers
stat.ME2024
Calibrated Model Criticism Using Split Predictive Checks
Jiawei Li, Jonathan H. Huggins
Checking how well a fitted model explains the data is one of the most fundamental parts of a Bayesian data analysis. However, existing model checking methods suffer from trade-offs…
stat.ML2024
A Framework for Improving the Reliability of Black-box Variational Inference
Manushi Welandawe, Michael Riis Andersen, Aki Vehtari +1
Black-box variational inference (BBVI) now sees widespread use in machine learning and statistics as a fast yet flexible alternative to Markov chain Monte Carlo methods for approxi…