Identifying nonlinear dynamical systems from multi-modal time series data. - Philine Lou Bommer; Daniel Kramer; Carlo Tombolini; Georgia Koppe; Daniel Durstewitz (CoRR, 2021)

Reconstructing Nonlinear Dynamical Systems from Multi-Modal Time Series. - Daniel Kramer; Philine Lou Bommer; Daniel Durstewitz; Carlo Tombolini; Georgia Koppe (ICML, 2022)

Finding the right XAI method - A Guide for the Evaluation and Ranking of Explainable AI Methods in Climate Science. - Philine Lou Bommer; Marlene Kretschmer; Anna Hedström; Dilyara Bareeva; Marina M.-C. Höhne (CoRR, 2023)

The Meta-Evaluation Problem in Explainable AI: Identifying Reliable Estimators with MetaQuantus. - Anna Hedström; Philine Lou Bommer; Kristoffer Knutsen Wickstrøm; Wojciech Samek; Sebastian Lapuschkin; Marina M.-C. Höhne (Trans. Mach. Learn. Res., 2023)

CoSy: Evaluating Textual Explanations of Neurons. - Laura Kopf; Philine Lou Bommer; Anna Hedström; Sebastian Lapuschkin; Marina M.-C. Höhne; Kirill Bykov (NeurIPS, 2024)

Evaluating Interpretable Methods via Geometric Alignment of Functional Distortions. - Anna Hedström; Philine Lou Bommer; Thomas F. Burns; Sebastian Lapuschkin; Wojciech Samek; Marina M.-C. Höhne (Trans. Mach. Learn. Res., 2025)

Deep Learning Meets Teleconnections: Improving S2S Predictions for European Winter Weather. - Philine Lou Bommer; Marlene Kretschmer; Fiona R. Spuler; Kirill Bykov; Marina M.-C. Höhne (CoRR, 2025)

Capturing Polysemanticity with PRISM: A Multi-Concept Feature Description Framework. - Laura Kopf; Nils Feldhus; Kirill Bykov; Philine Lou Bommer; Anna Hedström; Marina M.-C. Höhne; Oliver Eberle (CoRR, 2025)