Interpretable and Fine-Grained Visual Explanations for Convolutional Neural Networks. - Jörg Wagner; Jan Mathias Köhler; Tobias Gindele; Leon Hetzel; Jakob Thaddäus Wiedemer; Sven Behnke (CVPR, 2019)

Challenging Common Assumptions in Multi-task Learning. - Cathrin Elich; Lukas Kirchdorfer; Jan Mathias Köhler; Lukas Schott (CoRR, 2023)

Examining Common Paradigms in Multi-task Learning. - Cathrin Elich; Lukas Kirchdorfer; Jan Mathias Köhler; Lukas Schott (GCPR (1), 2024)

Analytical Uncertainty-Based Loss Weighting in Multi-task Learning. - Lukas Kirchdorfer; Cathrin Elich; Simon Kutsche; Heiner Stuckenschmidt; Lukas Schott; Jan Mathias Köhler (GCPR (1), 2024)

Mind the Gap Between Synthetic and Real: Utilizing Transfer Learning to Probe the Boundaries of Stable Diffusion Generated Data. - Leonhard Hennicke; Christian Medeiros Adriano; Holger Giese; Jan Mathias Köhler; Lukas Schott (CoRR, 2024)