Zobrazeno 1 - 10
of 253
pro vyhledávání: '"Steinbach Péter"'
Autor:
Reganova, Elizaveta, Steinbach, Peter
Large Language Models (LLMs) have gained significant popularity in recent years for their ability to answer questions in various fields. However, these models have a tendency to "hallucinate" their responses, making it challenging to evaluate their p
Externí odkaz:
http://arxiv.org/abs/2411.14465
Autor:
Korten, Till, Rybnikov, Vladimir, Vogt, Mathias, Roensch-Schulenburg, Juliane, Steinbach, Peter, Mirian, Najmeh
Electron beam accelerators are essential in many scientific and technological fields. Their operation relies heavily on the stability and precision of the electron beam. Traditional diagnostic techniques encounter difficulties in addressing the compl
Externí odkaz:
http://arxiv.org/abs/2411.09468
Instance segmentation has witnessed promising advancements through deep neural network-based algorithms. However, these models often exhibit incorrect predictions with unwarranted confidence levels. Consequently, evaluating prediction uncertainty bec
Externí odkaz:
http://arxiv.org/abs/2309.10513
Many deep learning methods have successfully solved complex tasks in computer vision and speech recognition applications. Nonetheless, the robustness of these models has been found to be vulnerable to perturbed inputs or adversarial examples, which a
Externí odkaz:
http://arxiv.org/abs/2206.08738
Autor:
Ferencz Csaba, Lizunov Georgii, Crespon François, Price Ivan, Bankov Ludmil, Przepiórka Dorota, Brieß Klaus, Dudkin Denis, Girenko Andrey, Korepanov Valery, Kuzmych Andrii, Skorokhod Tetiana, Marinov Pencho, Piankova Olena, Rothkaehl Hanna, Shtus Tetyana, Steinbach Péter, Lichtenberger János, Sterenharz Arnold, Vassileva Any
Publikováno v:
Journal of Space Weather and Space Climate, Vol 4, p A17 (2014)
In the frame of the FP7 POPDAT project the Ionosphere Waves Service (IWS) has been developed and opened for public access by ionosphere experts. IWS is forming a database, derived from archived ionospheric wave records to assist the ionosphere and Sp
Externí odkaz:
https://doaj.org/article/aa17f2e9201f4f76b9755a5635e4fe85
Autor:
Homeyer, André, Geißler, Christian, Schwen, Lars Ole, Zakrzewski, Falk, Evans, Theodore, Strohmenger, Klaus, Westphal, Max, Bülow, Roman David, Kargl, Michaela, Karjauv, Aray, Munné-Bertran, Isidre, Retzlaff, Carl Orge, Romero-López, Adrià, Sołtysiński, Tomasz, Plass, Markus, Carvalho, Rita, Steinbach, Peter, Lan, Yu-Chia, Bouteldja, Nassim, Haber, David, Rojas-Carulla, Mateo, Sadr, Alireza Vafaei, Kraft, Matthias, Krüger, Daniel, Fick, Rutger, Lang, Tobias, Boor, Peter, Müller, Heimo, Hufnagl, Peter, Zerbe, Norman
Publikováno v:
Mod Pathol (2022)
Artificial intelligence (AI) solutions that automatically extract information from digital histology images have shown great promise for improving pathological diagnosis. Prior to routine use, it is important to evaluate their predictive performance
Externí odkaz:
http://arxiv.org/abs/2204.14226
With the availability of data, hardware, software ecosystem and relevant skill sets, the machine learning community is undergoing a rapid development with new architectures and approaches appearing at high frequency every year. In this article, we co
Externí odkaz:
http://arxiv.org/abs/2204.05173
Autor:
Morimoto, Marie, Ryu, Eunjin, Steger, Benjamin J., Dixit, Abhijit, Saito, Yoshihiko, Yoo, Juyeong, van der Ven, Amelie T., Hauser, Natalie, Steinbach, Peter J., Oura, Kazumasa, Huang, Alden Y., Kortüm, Fanny, Ninomiya, Shinsuke, Rosenthal, Elisabeth A., Robinson, Hannah K., Guegan, Katie, Denecke, Jonas, Subramony, Sankarasubramoney H., Diamonstein, Callie J., Ping, Jie, Fenner, Mark, Balton, Elsa V., Strohbehn, Sam, Allworth, Aimee, Bamshad, Michael J., Gandhi, Mahi, Dipple, Katrina M., Blue, Elizabeth E., Jarvik, Gail P., Lau, C. Christopher, Holm, Ingrid A., Weisz-Hubshman, Monika, Solomon, Benjamin D., Nelson, Stanley F., Nishino, Ichizo, Adams, David R., Kang, Sukhyun, Gahl, William A., Toro, Camilo, Myung, Kyungjae, Malicdan, May Christine V.
Publikováno v:
In The American Journal of Human Genetics 5 September 2024 111(9):1970-1993
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