Search Results for author:
Found 2 papers, 1 papers with code
Leveraging Uncertainty Estimates To Improve Classifier Performance
Binary classification involves predicting the label of an instance based on whether the model score for the positive class exceeds a threshold chosen based on the application requirements (e. g., maximizing recall for a precision bound).
CRISP: A Probabilistic Model for Individual-Level COVID-19 Infection Risk Estimation Based on Contact Data
We present CRISP (COVID-19 Risk Score Prediction), a probabilistic graphical model for COVID-19 infection spread through a population based on the SEIR model where we assume access to (1) mutual contacts between pairs of individuals across time across various channels (e. g., Bluetooth contact traces), as well as (2) test outcomes at given times for infection, exposure and immunity tests.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
