Pascal Iversen

The paper demonstrates how to select synthetic data for transfer learning in dynamical biological systems, showing performance improvements of up to 92% in mean absolute error.

This paper benchmarks uncertainty-aware models for drug response prediction in cancer cell lines, finding ensemble-based methods better detect distribution shifts while distributional models reduce prediction errors in high-confidence subsets.

This paper evaluates drug response prediction models and finds that deep learning models perform similarly to simple baselines, highlighting issues in current model evaluation practices.