| Kurzfassung
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In our data-driven world where tons of data is collected, dependency estimation is an important tool to get more insight into our data. But 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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