HAPS constructs shorter conformal prediction sets for censored time-to-event outcomes by using time-varying covariate histories and IPCW, achieving approximate coverage among survivors with up to 75% shorter intervals in simulations.
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2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
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The paper releases a simulation dataset of 0νββ signal and 214Bi background events for the NEXT detector as educational material for an AI summer school.
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History-Aware Conformal Prediction Sets for Censored Time-to-Event Outcomes
HAPS constructs shorter conformal prediction sets for censored time-to-event outcomes by using time-varying covariate histories and IPCW, achieving approximate coverage among survivors with up to 75% shorter intervals in simulations.
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NEXT Simulation Dataset for AI Summer School UC Irvine 2026
The paper releases a simulation dataset of 0νββ signal and 214Bi background events for the NEXT detector as educational material for an AI summer school.