Patrick Michaelis
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View article: Data Analysis and Exploration with Computational Approaches
Data Analysis and Exploration with Computational Approaches Open
Artificial intelligence and machine learning (ML) methods are increasingly applied in Earth system research, for improving data analysis, and model performance, and eventually system understanding. In the Digital Earth project, several ML …
View article: Workflow towards autonomous and semi-automized UXO Survey and Detection
Workflow towards autonomous and semi-automized UXO Survey and Detection Open
This paper presents a workflow for UXO detection based on multibeam data in combination with AUV-based ground truth. An artificial neuronal network (ANN) is trained on manually annotated multibeam data and aims for making UXO detection and…
View article: Supplementary material to "GLODAPv2.2020 – the second update of GLODAPv2"
Supplementary material to "GLODAPv2.2020 – the second update of GLODAPv2" Open
The Global Ocean Data Analysis Project (GLODAP) is a synthesis effort providing regular compilations of surface to bottom ocean biogeochemical data, with an emphasis on seawater inorganic carbon chemistry and related variables determined t…
View article: Machine learning as supporting method for UXO mapping and detection
Machine learning as supporting method for UXO mapping and detection Open
<p>Marine munitions, or unexploded ordnances (UXO), were massively disposed of in coastal waters after World War II; they are still being introduced into the marine environment during war activities and military exercises. UXO detect…
View article: Mixed discrete‐continuous regression—A novel approach based on weight functions
Mixed discrete‐continuous regression—A novel approach based on weight functions Open
In a wide range of applications, standard regression techniques are hard to apply because the responses may consist of a continuous part but augmented with a discrete number of additional response categories with probability greater than z…
View article: Autoregressive effects in poll-based election models for the German federal election
Autoregressive effects in poll-based election models for the German federal election Open
Poll-based methods have been used to forecast elections in various countries and settings. A common factor of these models is the inclusion of a time-dependent variable to model the evolution of public support for a party or cause over tim…
View article: Bayesian Multivariate Distributional Regression With Skewed Responses and Skewed Random Effects
Bayesian Multivariate Distributional Regression With Skewed Responses and Skewed Random Effects Open
The normal and the t distribution are classical tools for building random effects regression models where both can be used for the specification of either the conditional response distribution or the random effects distribution. However, t…
View article: Bayesian Multivariate Distributional Regression with Skewed Responses and Skewed Random Effects
Bayesian Multivariate Distributional Regression with Skewed Responses and Skewed Random Effects Open
The normal and the t distribution are classical tools for building random effects regression models where both can be used for the specification of either the conditional response distribution or the random effects distribution. However, t…