Arun Kumar Kuchibhotla

13 catalog papers. Identity-linked publications and additional name matches are distinguished below.

ORCID: 0000-0003-4459-5352

Carnegie Mellon University

Publications

• Doubly robust and efficient calibration of prediction sets for right-censored time-to-event outcomes — Biometrika 2026
• Selection and Aggregation of Conformal Prediction Sets — Journal of the American Statistical Association 2025
• The HulC: confidence regions from convex hulls — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2024
• Doubly robust calibration of prediction sets under covariate shift — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2024
• Estimating the likelihood of arrest from police records in presence of unreported crimes — The Annals of Applied Statistics 2024
• Semiparametric Efficiency in Convexity Constrained Single-Index Model — Journal of the American Statistical Association 2023
• Nested conformal prediction sets for classification with applications to probation data — The Annals of Applied Statistics 2023
• Median regularity and honest inference — Biometrika 2023
• On least squares estimation under heteroscedastic and heavy-tailed errors — The Annals of Statistics 2022
• Andreas Buja, Richard A. Berk, Arun K. Kuchibhotla, Linda Zhao and Ed George’s contribution to the Discussion of ‘Assumption-lean inference for generalised linear model parameters’ by Vansteelandt and Dukes — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2022
• Elizabeth L Ogburn, Junhui Cai, Arun K Kuchibhotla, Richard A Berk and Andreas Buja’s contribution to the Discussion of ‘Assumption-lean inference for generalised linear model parameters’ by Vansteelandt and Dukes — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2022
• Valid post-selection inference in model-free linear regression — The Annals of Statistics 2020
• Theory for Identification and Inference with Synthetic Controls: A Proximal Causal Inference Framework — Journal of the American Statistical Association