4 citations · 5 across the 5 of their papers we have counts for
5 papers
An analysis of binary isotonic regression: degrees of freedom and implications for calibration
Raphael Rossellini, Rina Foygel Barber, Zhimei Ren +1
Isotonic regression is a canonical tool for estimating monotone functions and calibrating probabilistic predictors. We provide a fully sharp finite-sample characterization of its w…
Rigorous uncertainty quantification of probabilistic AI weather forecasts with conformal prediction
Anna Asch, Raphael Rossellini, Pedram Hassanzadeh +1
Probabilistic weather forecasting is undergoing rapid transformation with artificial intelligence (AI). In traditional numerical weather prediction, computing power can limit how w…
Can a calibration metric be both testable and actionable?
Raphael Rossellini, Jake A. Soloff, Rina Foygel Barber +2
Forecast probabilities often serve as critical inputs for binary decision making. In such settings, calibration$\unicode{x2014}$ensuring forecasted probabilities match empirical fr…
Integrating Uncertainty Awareness into Conformalized Quantile Regression
Raphael Rossellini, Rina Foygel Barber, Rebecca Willett
Conformalized Quantile Regression (CQR) is a recently proposed method for constructing prediction intervals for a response given covariates , without making distributional a…
Beyond Ensemble Averages: Leveraging Climate Model Ensembles for Subseasonal Forecasting
Elena Orlova, Haokun Liu, Raphael Rossellini +2
Producing high-quality forecasts of key climate variables, such as temperature and precipitation, on subseasonal time scales has long been a gap in operational forecasting. This st…