arXiv stat.ML
· Papers
Ribbon: Scalable Approximation and Robust Uncertainty Quantification
arXiv:2606.27269v1 Announce Type: new Abstract: Reliably quantifying predictive uncertainty is difficult for complex, high-dimensional, or misspecified models. Both fully Bayesian and bootstrap resampling methods provide principled uncertainty estimates but are often too expensive for modern machine-learning models bec