| Kurzfassung
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In our data-driven world, where tons of data are collected, dependency estimation is important to get more insights into our data. Many dependency estimation algorithms are hard to use in a real-world setting. In this study, I will do a comparison of different state-of-the-art dependency estimation algorithms. For comparison, a list of different criteria is used and the focus of this study is on data efficiency and uncertainty of the dependency estimation algorithms. The comparison includes a theoretical analysis and a variety of different experiments with an implementation of the dependency estimation algorithm that performed well in the theoretical analysis.
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