8 papers
Robust Bayes-Assisted Conformal Prediction
Kianoosh Ashouritaklimi, Stefano Cortinovis, François Caron
Bayes-assisted conformal prediction combines the strengths of Bayesian modelling with exact, distribution-free frequentist coverage guarantees. Although conformal validity is prese…
Bayes-assisted Confidence Regions: Focal Point Estimator and Bounded-influence Priors
Stefano Cortinovis, François Caron
The Frequentist, Assisted by Bayes (FAB) framework constructs confidence regions that leverage prior information about parameter values. FAB confidence regions (FAB-CRs) have small…
Variational predictive resampling
Laura Battaglia, Stefano Cortinovis, Chris Holmes +2
Bayesian inference provides principled uncertainty quantification, but accurate posterior sampling with MCMC can be computationally prohibitive for modern applications. Variational…
Asymptotically Log-Optimal Bayes-Assisted Confidence Sequences for Bounded Means
Valentin Kilian, Stefano Cortinovis, François Caron
Confidence sequences based on test martingales provide time-uniform uncertainty quantification for the mean of bounded IID observations without parametric distributional assumption…
Confidence sequences with informative, bounded-influence priors
Stefano Cortinovis, Valentin Kilian, François Caron
Confidence sequences are collections of confidence regions that simultaneously cover the true parameter for every sample size at a prescribed confidence level. Tightening these seq…
Inverse-Free Sparse Variational Gaussian Processes
Stefano Cortinovis, Laurence Aitchison, Stefanos Eleftheriadis +1
Gaussian processes (GPs) offer appealing properties but are costly to train at scale. Sparse variational GP (SVGP) approximations reduce cost yet still rely on Cholesky decompositi…