Interval Neural Networks: Uncertainty Scores. - Luis Oala; Cosmas Heiss; Jan MacDonald; Maximilian März; Wojciech Samek; Gitta Kutyniok (CoRR, 2020)

In-Distribution Interpretability for Challenging Modalities. - Cosmas Heiß; Ron Levie; Cinjon Resnick; Gitta Kutyniok; Joan Bruna (CoRR, 2020)

Detecting failure modes in image reconstructions with interval neural network uncertainty. - Luis Oala; Cosmas Heiß; Jan MacDonald; Maximilian März; Gitta Kutyniok; Wojciech Samek (Int. J. Comput. Assist. Radiol. Surg., 2021)

Self-Supervised Equivariant Scene Synthesis from Video. - Cinjon Resnick; Or Litany; Cosmas Heiß; Hugo Larochelle; Joan Bruna; Kyunghyun Cho (CoRR, 2021)

Lagrangian Motion Magnification with Landmark-Prior and Sparse PCA for Facial Microexpressions and Micromovements. - Philipp Flotho; Cosmas Heiß; Gabriele Steidl; Daniel J. Strauss (EMBC, 2022)

Lagrangian motion magnification with double sparse optical flow decomposition. - Philipp Flotho; Cosmas Heiss; Gabriele Steidl; Daniel J. Strauss (Frontiers Appl. Math. Stat., 2023)

Multilevel CNNs for Parametric PDEs. - Cosmas Heiß; Ingo Gühring; Martin Eigel (J. Mach. Learn. Res., 2023)

On Assignment Problems Related to Gromov-Wasserstein Distances on the Real Line. - Robert Beinert; Cosmas Heiss; Gabriele Steidl (SIAM J. Imaging Sci., 2023)

Multi-level Neural Networks for high-dimensional parametric obstacle problems. - Martin Eigel; Cosmas Heiß; Janina E. Schütte (CoRR, 2025)