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Found 5 papers, 1 papers with code
Redistributor: Transforming Empirical Data Distributions
When given independent and identically distributed samples of some random variable $S$ and the continuous cumulative distribution function of some desired target $T$, it provably produces a consistent estimator of the transformation $R$ which satisfies $R(S)=T$ in distribution.
Robust models of SARS-CoV-2 heterogeneity and control
Our simulation functions as a dynamic compartment model in which an individual's history of infection, vaccination, and possible reinfection all play a role in their resistance to further infections.
Evidence suggests that SARS-CoV-2 rapid antigen tests provide benefits for epidemic control -- observations from Austrian schools
Rapid antigen tests detect proteins at the surface of virus particles, identifying the disease during its infectious phase.
Disease Momentum: Estimating the Reproduction Number in the Presence of Superspreading
Our models demonstrate that the estimation uncertainty of the reproduction number increases with superspreading and that this improves the performance of prediction intervals.
Adaptive, Distribution-Free Prediction Intervals for Deep Networks
The machine learning literature contains several constructions for prediction intervals that are intuitively reasonable but ultimately ad-hoc in that they do not come with provable performance guarantees.
