Hanne Raum

This study evaluates process-guided neural networks (PGNNs) and standard ANNs for predicting forest carbon fluxes, showing PGNNs outperform a process model in data-sparse and transfer scenarios.

This paper proposes a deep learning method to align neural network architectures across species for single-cell data, revealing commonalities and differences in gene expression.