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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A Bayesian mixed Hawkes process with Weibull baseline intensity and random effects is developed to model seizure clustering and heterogeneity in focal epilepsy from the Human Epilepsy Project data.
GAPS has constructed and launched a stratospheric balloon spectrometer that uses silicon trackers and TOF detectors to identify low-energy antiprotons, antideuterons, and antihelium via exotic-atom formation and annihilation products.
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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A Mixed Self-Exciting Process to Model Epileptic Seizures
A Bayesian mixed Hawkes process with Weibull baseline intensity and random effects is developed to model seizure clustering and heterogeneity in focal epilepsy from the Human Epilepsy Project data.