10.25678/00035V
Ramgraber, M.
M.
Ramgraber
https://orcid.org/0000-0003-3508-6214
Eawag: Swiss Federal Institute of Aquatic Science and Technology
Weatherl, R.
R.
Weatherl
https://orcid.org/0000-0003-4965-3734
Eawag: Swiss Federal Institute of Aquatic Science and Technology
Blumensaat, F.
F.
Blumensaat
https://orcid.org/0000-0002-0742-7950
Eawag: Swiss Federal Institute of Aquatic Science and Technology
Schirmer, M.
M.
Schirmer
https://orcid.org/0000-0002-0714-2525
Eawag: Swiss Federal Institute of Aquatic Science and Technology
Data for: Non‐Gaussian parameter inference for hydrogeological models using Stein Variational Gradient Descent
Eawag: Swiss Federal Institute of Aquatic Science and Technology
2021
Publication Data Package
groundwater
river
aquifer
Bayesian inference
Bayesian statistics
Jacobian
SVGD
Stein Variational Gradient Descent
ensemble-based
hydrogeology
modeling
modelling
non-Gaussian
2021-03-26
2017-06/2018-12
2021
en
10.1029/2020wr029339
10.1029/2020wr029339
1.0
Creative Commons Zero v1.0 Universal
This package includes the data and Python files for the publication "Non‐Gaussian parameter inference for hydrogeological models using Stein Variational Gradient Descent".
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