A Call to Reflect on Evaluation Practices for Failure Detection in Image Classification. - Paul F. Jaeger; Carsten T. Lüth; Lukas Klein; Till J. Bungert (ICLR, 2023)

Understanding Silent Failures in Medical Image Classification. - Till J. Bungert; Levin Kobelke; Paul F. Jäger (MICCAI (3), 2023)

Navigating the Pitfalls of Active Learning Evaluation: A Systematic Framework for Meaningful Performance Assessment. - Carsten T. Lüth; Till J. Bungert; Lukas Klein; Paul F. Jaeger (NeurIPS, 2023)

Toward Realistic Evaluation of Deep Active Learning Algorithms in Image Classification. - Carsten T. Lüth; Till J. Bungert; Lukas Klein; Paul F. Jaeger (CoRR, 2023)

Abstract: Understanding Silent Failures in Medical Image Classification. - Till J. Bungert; Levin Kobelke; Paul F. Jaeger (Bildverarbeitung für die Medizin, 2024)

Navigating the Maze of Explainable AI: A Systematic Approach to Evaluating Methods and Metrics. - Lukas Klein; Carsten T. Lüth; Udo Schlegel; Till J. Bungert; Mennatallah El-Assady; Paul F. Jaeger (NeurIPS, 2024)

Overcoming Common Flaws in the Evaluation of Selective Classification Systems. - Jeremias Traub; Till J. Bungert; Carsten T. Lüth; Michael Baumgartner 001; Klaus H. Maier-Hein; Lena Maier-Hein; Paul F. Jaeger (NeurIPS, 2024)

nnActive: A Framework for Evaluation of Active Learning in 3D Biomedical Segmentation. - Carsten T. Lüth; Jeremias Traub; Kim-Celine Kahl; Till J. Bungert; Lukas Klein; Lars Krämer; Paul F. Jaeger; Fabian Isensee; Klaus H. Maier-Hein (Trans. Mach. Learn. Res., 2025)