| 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. I will compare them regarding a list of different criteria and focus on data efficiency and uncertainty of the estimation. The comparison includes a theoretical analysis and a variety of different experiments with the algorithms.
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