Zobrazeno 1 - 10
of 1 530
pro vyhledávání: '"Till, J."'
Autor:
Klein, Lukas, Lüth, Carsten T., Schlegel, Udo, Bungert, Till J., El-Assady, Mennatallah, Jäger, Paul F.
Explainable AI (XAI) is a rapidly growing domain with a myriad of proposed methods as well as metrics aiming to evaluate their efficacy. However, current studies are often of limited scope, examining only a handful of XAI methods and ignoring underly
Externí odkaz:
http://arxiv.org/abs/2409.16756
Autor:
Traub, Jeremias, Bungert, Till J., Lüth, Carsten T., Baumgartner, Michael, Maier-Hein, Klaus H., Maier-Hein, Lena, Jaeger, Paul F
Selective Classification, wherein models can reject low-confidence predictions, promises reliable translation of machine-learning based classification systems to real-world scenarios such as clinical diagnostics. While current evaluation of these sys
Externí odkaz:
http://arxiv.org/abs/2407.01032
Autor:
Christina Sauer, Till Hansen, Holly G. Prigerson, Jennifer W. Mack, Till J. Bugaj, Gregor Weißflog
Publikováno v:
BMC Psychology, Vol 12, Iss 1, Pp 1-10 (2024)
Abstract Background Systematic reviews and meta-analyses reveal the importance of an accepting attitude towards cancer for mental health and functional coping. The aim of this study was to examine the psychometric properties of the German translation
Externí odkaz:
https://doaj.org/article/7094d360b87f4bdd913e0dbd97a62d99
To ensure the reliable use of classification systems in medical applications, it is crucial to prevent silent failures. This can be achieved by either designing classifiers that are robust enough to avoid failures in the first place, or by detecting
Externí odkaz:
http://arxiv.org/abs/2307.14729
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 research on improving AL query methods in recent years, some studies have qu
Externí odkaz:
http://arxiv.org/abs/2301.10625
Autor:
Anthony C. Leung, W. Y. Sarah Lau, Aaron D. Tranter, Karun V. Paul, Markus Rambach, Ben C. Buchler, Ping Koy Lam, Andrew G. White, Till J. Weinhold
Publikováno v:
APL Quantum, Vol 1, Iss 3, Pp 036102-036102-7 (2024)
Efficient quantum memories will be an essential building block of large-scale networked quantum systems and provide a link between flying photonic qubits and atomic or quasi-atomic local quantum processors. Memory efficiencies above 50% are required
Externí odkaz:
https://doaj.org/article/dc3e100874254590a38c360fda404448
Publikováno v:
ICLR 2023 (oral)
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 approaches aims to detect erroneous predictions by means of assigning confi
Externí odkaz:
http://arxiv.org/abs/2211.15259
Publikováno v:
Beilstein Journal of Organic Chemistry, Vol 20, Iss 1, Pp 1236-1245 (2024)
Organic photocatalysts frequently possess dual singlet and triplet photoreactivity and a thorough photochemical characterization is essential for efficient light-driven applications. In this article, the mode of action of a polyazahelicene catalyst (
Externí odkaz:
https://doaj.org/article/0cde951230e4418a8e55ba6819d60c06
Publikováno v:
Ecology and Evolution, Vol 14, Iss 6, Pp n/a-n/a (2024)
Abstract An increasing number of studies in botanical gardens are investigating species' responses to climate change. However, the influence of local environmental or habitat conditions such as soil nutrient status or microclimate on phenology and th
Externí odkaz:
https://doaj.org/article/b4305ffb2f5a4daba5160b6327953d7a