Guided Image Generation with Conditional Invertible Neural Networks. - Lynton Ardizzone; Carsten T. Lüth; Jakob Kruse; Carsten Rother; Ullrich Köthe (CoRR, 2019)

Conditional Invertible Neural Networks for Diverse Image-to-Image Translation. - Lynton Ardizzone; Jakob Kruse; Carsten T. Lüth; Niels Bracher; Carsten Rother; Ullrich Köthe (GCPR, 2020)

Unsupervised Anomaly Detection in the Wild. - David Zimmerer; Daniel Paech; Carsten T. Lüth; Jens Petersen; Gregor Köhler; Klaus H. Maier-Hein (Bildverarbeitung für die Medizin, 2022)

Contrastive Representations for Unsupervised Anomaly Detection and Localization. - Carsten T. Lüth; David Zimmerer; Gregor Köhler; Paul F. Jaeger; Fabian Isensee; Klaus H. Maier-Hein (Bildverarbeitung für die Medizin, 2023)

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)

cOOpD: Reformulating COPD Classification on Chest CT Scans as Anomaly Detection Using Contrastive Representations. - Silvia Dias Almeida; Carsten T. Lüth; Tobias Norajitra; Tassilo Wald; Marco Nolden; Paul F. Jäger; Claus Peter Heussel; Jürgen Biederer; Oliver Weinheimer; Klaus H. Maier-Hein (MICCAI (5), 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)

CRADL: Contrastive Representations for Unsupervised Anomaly Detection and Localization. - Carsten T. Lüth; David Zimmerer; Gregor Köhler; Paul F. Jaeger; Fabian Isensee; Jens Petersen; Klaus H. Maier-Hein (CoRR, 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: Reformulating COPD Classification on Chest CT Scans as Anomaly Detection using Contrastive Representations - cOOpD. - Silvia Dias Almeida; Carsten T. Lüth; Tobias Norajitra; Tassilo Wald; Marco Nolden; Paul F. Jäger; Claus Peter Heussel; Jürgen Biederer; Oliver Weinheimer; Klaus H. Maier-Hein (Bildverarbeitung für die Medizin, 2024)

ValUES: A Framework for Systematic Validation of Uncertainty Estimation in Semantic Segmentation. - Kim-Celine Kahl; Carsten T. Lüth; Maximilian Zenk; Klaus H. Maier-Hein; Paul F. Jaeger (ICLR, 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)

Embarrassingly Simple Scribble Supervision for 3D Medical Segmentation. - Karol Gotkowski; Carsten T. Lüth; Paul F. Jäger; Sebastian Ziegler; Lars Krämer; Stefan Denner; Shuhan Xiao; Nico Disch; Klaus H. Maier-Hein; Fabian Isensee (CoRR, 2024)

Why context matters in VQA and Reasoning: Semantic interventions for VLM input modalities. - Kenza Amara; Lukas Klein; Carsten T. Lüth; Paul Jäger 002; Hendrik Strobelt; Mennatallah El-Assady (CoRR, 2024)

SURE-VQA: Systematic Understanding of Robustness Evaluation in Medical VQA Tasks. - Kim-Celine Kahl; Selen Erkan; Jeremias Traub; Carsten T. Lüth; Klaus H. Maier-Hein; Lena Maier-Hein; Paul F. Jaeger (Trans. Mach. Learn. Res., 2025)