Search Results for author: Julian Kappler

Found 2 papers, 2 papers with code

Efficient Bayesian inference of fully stochastic epidemiological models with applications to COVID-19

2 code implementations21 Oct 2020 Yuting I. Li, Günther Turk, Paul B. Rohrbach, Patrick Pietzonka, Julian Kappler, Rajesh Singh, Jakub Dolezal, Timothy Ekeh, Lukas Kikuchi, Joseph D. Peterson, Hideki Kobayashi, Michael E. Cates, R. Adhikari, Robert L. Jack

Epidemiological forecasts are beset by uncertainties about the underlying epidemiological processes, and the surveillance process through which data are acquired.

Methodology Populations and Evolution

Inference, prediction and optimization of non-pharmaceutical interventions using compartment models: the PyRoss library

1 code implementation19 May 2020 R. Adhikari, Austen Bolitho, Fernando Caballero, Michael E. Cates, Jakub Dolezal, Timothy Ekeh, Jules Guioth, Robert L. Jack, Julian Kappler, Lukas Kikuchi, Hideki Kobayashi, Yuting I. Li, Joseph D. Peterson, Patrick Pietzonka, Benjamin Remez, Paul B. Rohrbach, Rajesh Singh, Günther Turk

The PyRoss library enables fitting to epidemiological data, as available, using Bayesian parameter inference, so that competing models can be weighed by their evidence.

Populations and Evolution Physics and Society Quantitative Methods

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