81 to 90 of 188 Results
Apr 9, 2025 -
Replication Data for: An entropy-based evaluation of conceptual constraints in hybrid hydrological models
Plain Text - 940 B -
MD5: 9df9f1b9d57bf3ad026c33dd22688a2b
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Apr 9, 2025 -
Replication Data for: An entropy-based evaluation of conceptual constraints in hybrid hydrological models
Jupyter Notebook - 77.9 KB -
MD5: 64985de605105262d97f2e9e4a4a8556
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Apr 9, 2025 -
Replication Data for: An entropy-based evaluation of conceptual constraints in hybrid hydrological models
Python Source Code - 18.4 KB -
MD5: 4fc8b8900e22952ac96c1f2a77635b92
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Apr 9, 2025 -
Replication Data for: An entropy-based evaluation of conceptual constraints in hybrid hydrological models
Python Source Code - 12.3 KB -
MD5: 3f8043e07e594648e098a3b5045aee5d
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Apr 9, 2025 -
Replication Data for: An entropy-based evaluation of conceptual constraints in hybrid hydrological models
Python Source Code - 10.3 KB -
MD5: ae4b05e3488f75cf7a425a65ab988d7b
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Apr 9, 2025 -
Replication Data for: An entropy-based evaluation of conceptual constraints in hybrid hydrological models
Python Source Code - 975 B -
MD5: bdfcdc29a422859173711c627dc6878e
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Apr 9, 2025 -
Replication Data for: An entropy-based evaluation of conceptual constraints in hybrid hydrological models
Python Source Code - 21.3 KB -
MD5: 933984ef65287c1314b907e614c6067c
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Apr 9, 2025 -
Replication Data for: An entropy-based evaluation of conceptual constraints in hybrid hydrological models
ZIP Archive - 18.4 KB -
MD5: 934d31b87c9e5e48157bfa0734edaea9
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Jun 18, 2024
Álvarez Chaves, Manuel; Ehret, Uwe; Guthke, Anneli, 2024, "UNITE Toolbox", https://doi.org/10.18419/DARUS-4188, DaRUS, V1
UNITE Toolbox Unified diagnostic evaluation of scientific models based on information theory The UNITE Toolbox is a Python library for incorporating Information Theory into data analysis and modeling workflows. The toolbox collects different methods of estimating information-theoretic quantities in one easy-to-use Python package. Currently, UNITE i... |
Jun 18, 2024 -
UNITE Toolbox
Python Source Code - 1.6 KB -
MD5: bae1019ad6ad6c0e05d7e30f8b333ebc
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