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Bayesian hierarchical models can infer interpretable predictions of leaf area index from heterogeneous datasets
View ORCID ProfileOlivera Stojanović, Bastian Siegmann, Thomas Jarmer, Gordon Pipa, Johannes Leugering
doi: https://doi.org/10.1101/2021.09.20.461084
Olivera Stojanović
1University of Osnabrück, Institute of Cognitive Science, Osnabrück, Germany
Bastian Siegmann
2Jülich Research Centre, Institute of Bio- and Geosciences, Jülich, Germany
Thomas Jarmer
3University of Osnabrück, Institute of Computer Science, Osnabrück, Germany
Gordon Pipa
1University of Osnabrück, Institute of Cognitive Science, Osnabrück, Germany
Johannes Leugering
1University of Osnabrück, Institute of Cognitive Science, Osnabrück, Germany
Posted September 23, 2021.
Bayesian hierarchical models can infer interpretable predictions of leaf area index from heterogeneous datasets
Olivera Stojanović, Bastian Siegmann, Thomas Jarmer, Gordon Pipa, Johannes Leugering
bioRxiv 2021.09.20.461084; doi: https://doi.org/10.1101/2021.09.20.461084
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