18 citations · 32 across the 7 of their papers we have counts for
7 papers
Physics-IQ Verified
Tim Rädsch, Yuki M Asano, Hilde Kuehne +4
Video generative models ( VGMs) have become a new frontier that can be used not just for video generation but for a multitude of downstream tasks, including world modeling. To adva…
Overcoming Common Flaws in the Evaluation of Selective Classification Systems
Jeremias Traub, Till J. Bungert, Carsten T. Lüth +4
Selective Classification, wherein models can reject low-confidence predictions, promises reliable translation of machine-learning based classification systems to real-world scenari…
ValUES: A Framework for Systematic Validation of Uncertainty Estimation in Semantic Segmentation
Kim-Celine Kahl, Carsten T. Lüth, Maximilian Zenk +2
Uncertainty estimation is an essential and heavily-studied component for the reliable application of semantic segmentation methods. While various studies exist claiming methodologi…
cOOpD: Reformulating COPD classification on chest CT scans as anomaly detection using contrastive representations
Silvia D. Almeida, Carsten T. Lüth, Tobias Norajitra +7
Classification of heterogeneous diseases is challenging due to their complexity, variability of symptoms and imaging findings. Chronic Obstructive Pulmonary Disease (COPD) is a pri…
CRADL: Contrastive Representations for Unsupervised Anomaly Detection and Localization
Carsten T. Lüth, David Zimmerer, Gregor Koehler +4
Unsupervised anomaly detection in medical imaging aims to detect and localize arbitrary anomalies without requiring annotated anomalous data during training. Often, this is achieve…
Navigating the Pitfalls of Active Learning Evaluation: A Systematic Framework for Meaningful Performance Assessment
Carsten T. Lüth, Till J. Bungert, Lukas Klein +1
Active Learning (AL) aims to reduce the labeling burden by interactively selecting the most informative samples from a pool of unlabeled data. While there has been extensive resear…
A Call to Reflect on Evaluation Practices for Failure Detection in Image Classification
Paul F. Jaeger, Carsten T. Lüth, Lukas Klein +1
Reliable application of machine learning-based decision systems in the wild is one of the major challenges currently investigated by the field. A large portion of established appro…