Advanced Bayesian inference with stochastic hydrological models
Description
With advanced numerical techniques, including Approximate Bayesian Computation (ABC), Hamiltonian Monte Carlo (HMC) and Machine Learning (ML), we want to push the limits of Bayesian inference with stochastic models. The focus of the application will be on the hydrological sciences.
Key Data
Projectlead
Dr. Carlo Albert
Project team
Project partners
Eidgenössische Anstalt für Wasserversorgung, Abwasserreinigung und Gewässerschutz eawag / Department Systems Analysis, Integrated Assessment and Modelling
Project status
completed, 04/2017 - 06/2022
Funding partner
SNF-Projektförderung / Projekt Nr. 169295
