In this project, we will employ deep learning techniques to enhance the accuracy, interpretability, and robustness of indirect measurements. Particularly, we focus on problems of i) interpretation and analysis of metagenomic data obtained from agricultural soil samples, characterized by high-dimensional feature spaces with a relatively small number of soil samples (for an overview, see [1]-[4]), […]
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