Zobrazeno 1 - 10
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pro vyhledávání: '"Brenning, A"'
Autor:
Brenning, Alexander, Henn, Sebastian
With much of our lives taking place online, researchers are increasingly turning to information from the World Wide Web to gain insights into geographic patterns and processes. Web scraping as an online data acquisition technique allows us to gather
Externí odkaz:
http://arxiv.org/abs/2305.19893
Publikováno v:
Geoderma, Vol 448, Iss , Pp 116953- (2024)
Soil organic carbon (SOC) plays a crucial role in the global carbon cycle and in maintaining soil functions in the context of land use and climate change. Understanding the spatial distribution of SOC is essential for the management of agricultural l
Externí odkaz:
https://doaj.org/article/c99d890cb0bd4d99a9fa2a6de32e6703
Autor:
Shijie Jiang, Lily‐belle Sweet, Georgios Blougouras, Alexander Brenning, Wantong Li, Markus Reichstein, Joachim Denzler, Wei Shangguan, Guo Yu, Feini Huang, Jakob Zscheischler
Publikováno v:
Earth's Future, Vol 12, Iss 7, Pp n/a-n/a (2024)
Abstract Interpretable Machine Learning (IML) has rapidly advanced in recent years, offering new opportunities to improve our understanding of the complex Earth system. IML goes beyond conventional machine learning by not only making predictions but
Externí odkaz:
https://doaj.org/article/eb521b00c73e49509e141f1f17007bc6
Autor:
Schäfer, Susann, Brenning, Alexander
Publikováno v:
In Progress in Economic Geography December 2024 2(2)
Autor:
Suesse, Thomas b, a, c, ⁎, Brenning, Alexander c, d
Publikováno v:
In Spatial Statistics March 2025 65
Autor:
Brenning, Alexander
While significant progress has been made towards explaining black-box machine-learning (ML) models, there is still a distinct lack of diagnostic tools that elucidate the spatial behaviour of ML models in terms of predictive skill and variable importa
Externí odkaz:
http://arxiv.org/abs/2111.08478
Spatial and spatiotemporal machine-learning models require a suitable framework for their model assessment, model selection, and hyperparameter tuning, in order to avoid error estimation bias and over-fitting. This contribution reviews the state-of-t
Externí odkaz:
http://arxiv.org/abs/2110.12674
Autor:
Ekeroth, Sebastian, Ekspong, Joakim, Sharma, Sachin, Boyd, Robert, Brenning, Nils, Gracia-Espino, Eduardo, Edman, Ludvig, Helmerssona, Ulf, Wågberg, Thomas
The hydrogen evolution reaction (HER) is a key process in electrochemical water splitting. To lower the cost and environmental impact of this process, it is highly motivated to develop electrocatalysts with low or no content of noble metals. Here we
Externí odkaz:
http://arxiv.org/abs/2110.08006
Autor:
Brenning, Alexander
Model-agnostic tools for interpreting machine-learning models struggle to summarize the joint effects of strongly dependent features in high-dimensional feature spaces, which play an important role in pattern recognition, for example in remote sensin
Externí odkaz:
http://arxiv.org/abs/2104.04295