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We address the calibration of SEIR-like epidemiological models from daily reports of COVID-19 infections in New York City, during the period 01-Mar-2020 to 22-Aug-2020. Our models account for different types of disease severity, age range, sex and spatial distribution. The manuscript related to such simulations can be found in https://arxiv.org/…
In this problem statement, a sequence of genetic mutations and clinical evidences, i.e. descriptive texts as recorded by domain experts are used to classify the mutations to conclusive categories, to be used for diagnosis of the patient.
This is the official PyTorch codebase for the ACL 2023 paper: "What are the Desired Characteristics of Calibration Sets? Identifying Correlates on Long Form Scientific Summarization".
This instruction aims to reproduce the results in the paper “Calibration of inexact computer models with heteroscedastic errors” proposed by Sung, Barber, and Walker (2022).
This R package allows calibration parameter estimation for inexact computer models with heteroscedastic errors proposed by Sung, Barber, and Walker (2022) in SIAM/ASA Journal on Uncertainty Quantification.
An application of NLP and classical ML algorithms to an interesting real-world use case of predicting similarity between two questions on Quora. This allows the platform to combine similar questions into one and combine their answers to avoid duplication and unnecessary confusion.