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Madlene Nussbaum

Showing results (1-10 of 5) with videos related to

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The Science of the Total Environment|December 1, 2020
Mapping the geogenic radon potential for Germany by machine learningEric Petermann, Hanna Meyer, Madlene Nussbaum, et al.
The Science of the Total Environment|September 30, 2024
Landscape metrics as predictors of water-related ecosystem services: Insights from hydrological modeling and data-based approaches applied on the Arno River Basin, ItalyJerome El Jeitany, Madlene Nussbaum, Tommaso Pacetti, et al.
Journal of Equine Veterinary Science|August 19, 2023
Large Temporal Variations of Functional Properties of Outdoor Equestrian Arena Surfaces and a New Concept of Evaluating Reactivity With Light Weight Deflectometer Settlement CurvesConny Herholz, Janina Siegwart, Madlene Nussbaum, et al.
Peerj|September 7, 2018
Random forest as a generic framework for predictive modeling of spatial and spatio-temporal variablesTomislav Hengl, Madlene Nussbaum, Marvin N Wright, et al.
Scientific Data|July 4, 2026
GLORIF1, a global river flow dataset created by integrating process-based modelling and machine learningSümeyye Büşra Işık, Oriol Pomarol Moya, Michele Magni, et al.
Pageof 1

Showing results (1-10 of 5) with videos related to

Sort By:
Pageof 1
The Science of the Total Environment|December 1, 2020
Mapping the geogenic radon potential for Germany by machine learningEric Petermann, Hanna Meyer, Madlene Nussbaum, et al.
The Science of the Total Environment|September 30, 2024
Landscape metrics as predictors of water-related ecosystem services: Insights from hydrological modeling and data-based approaches applied on the Arno River Basin, ItalyJerome El Jeitany, Madlene Nussbaum, Tommaso Pacetti, et al.
Journal of Equine Veterinary Science|August 19, 2023
Large Temporal Variations of Functional Properties of Outdoor Equestrian Arena Surfaces and a New Concept of Evaluating Reactivity With Light Weight Deflectometer Settlement CurvesConny Herholz, Janina Siegwart, Madlene Nussbaum, et al.
Peerj|September 7, 2018
Random forest as a generic framework for predictive modeling of spatial and spatio-temporal variablesTomislav Hengl, Madlene Nussbaum, Marvin N Wright, et al.
Scientific Data|July 4, 2026
GLORIF1, a global river flow dataset created by integrating process-based modelling and machine learningSümeyye Büşra Işık, Oriol Pomarol Moya, Michele Magni, et al.
Pageof 1