289 citations · 1.2k across the 72 of their papers we have counts for
3 papers · 2 filters
Fast, Distribution-free Predictive Inference for Neural Networks with Coverage Guarantees
Yue Gao, Garvesh Raskutti, Rebecca Willet
This paper introduces a novel, computationally-efficient algorithm for predictive inference (PI) that requires no distributional assumptions on the data and can be computed faster…
Reduced-Order Autodifferentiable Ensemble Kalman Filters
Yuming Chen, Daniel Sanz-Alonso, Rebecca Willett
This paper introduces a computational framework to reconstruct and forecast a partially observed state that evolves according to an unknown or expensive-to-simulate dynamical syste…
Bagging Provides Assumption-free Stability
Jake A. Soloff, Rina Foygel Barber, Rebecca Willett
Bagging is an important technique for stabilizing machine learning models. In this paper, we derive a finite-sample guarantee on the stability of bagging for any model. Our result…