7 papers
Conformal Prediction for Regression with Clipped Outcomes
Matteo Sesia, Vladimir Svetnik
We study conformal prediction for regression using calibration data with outcomes that are doubly censored (clipped) at known fixed thresholds. We show that existing methods are un…
Collective Outlier Detection and Enumeration with Conformalized Closed Testing
Chiara G. Magnani, Matteo Sesia, Aldo Solari
This paper develops a flexible distribution-free method for collective outlier detection and enumeration, designed for situations in which the presence of outliers can be detected…
Elements of Conformal Prediction for Statisticians
Matteo Sesia, Stefano Favaro
Predictive inference is a fundamental task in statistics, traditionally addressed using parametric assumptions about the data distribution and detailed analyses of how models learn…
Distribution-Free Selection of Low-Risk Oncology Patients for Survival Beyond a Time Horizon
Matteo Sesia, Vladimir Svetnik
We study the problem of selecting a subset of patients who are unlikely to experience an adverse event within a fixed time horizon by calibrating a screening rule based on a black-…
Interpretable Multivariate Conformal Prediction with Fast Transductive Standardization
Yunjie Fan, Matteo Sesia
We propose a conformal prediction method for constructing tight simultaneous prediction intervals for multiple, potentially related, numerical outputs given a single input. This me…
Conformal Survival Bands for Risk Screening under Right-Censoring
Matteo Sesia, Vladimir Svetnik
We propose a method to quantify uncertainty around individual survival distribution estimates using right-censored data, compatible with any survival model. Unlike classical confid…