Zobrazeno 1 - 10
of 1 504
pro vyhledávání: '"P. Obrist"'
Autor:
T. Hautz, S. Salcher, M. Fodor, G. Sturm, S. Ebner, A. Mair, M. Trebo, G. Untergasser, S. Sopper, B. Cardini, A. Martowicz, J. Hofmann, S. Daum, M. Kalb, T. Resch, F. Krendl, A. Weissenbacher, G. Otarashvili, P. Obrist, B. Zelger, D. Öfner, Z. Trajanoski, J. Troppmair, R. Oberhuber, A. Pircher, D. Wolf, S. Schneeberger
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-18 (2023)
Abstract Normothermic machine perfusion (NMP) has emerged as an innovative organ preservation technique. Developing an understanding for the donor organ immune cell composition and its dynamic changes during NMP is essential. We aimed for a comprehen
Externí odkaz:
https://doaj.org/article/6155b582850748e78479b29cb2a4182a
Aligning AI with human intent is important, yet perceptual alignment-how AI interprets what we see, hear, or smell-remains underexplored. This work focuses on olfaction, human smell experiences. We conducted a user study with 40 participants to inves
Externí odkaz:
http://arxiv.org/abs/2411.06950
Autor:
Obrist, Jan, Zamora, Miguel, Zheng, Hehui, Hinchet, Ronan, Ozdemir, Firat, Zarate, Juan, Katzschmann, Robert K., Coros, Stelian
Data-driven methods have shown great potential in solving challenging manipulation tasks, however, their application in the domain of deformable objects has been constrained, in part, by the lack of data. To address this, we propose PokeFlex, a datas
Externí odkaz:
http://arxiv.org/abs/2410.07688
Autor:
Obrist, Jan, Zamora, Miguel, Zheng, Hehui, Zarate, Juan, Katzschmann, Robert K., Coros, Stelian
Advancing robotic manipulation of deformable objects can enable automation of repetitive tasks across multiple industries, from food processing to textiles and healthcare. Yet robots struggle with the high dimensionality of deformable objects and the
Externí odkaz:
http://arxiv.org/abs/2409.17124
Developing domain-specific conversational agents (CAs) has been challenged by the need for extensive domain-focused data. Recent advancements in Large Language Models (LLMs) make them a viable option as a knowledge backbone. LLMs behaviour can be enh
Externí odkaz:
http://arxiv.org/abs/2406.10590
Aligning large language models (LLMs) behaviour with human intent is critical for future AI. An important yet often overlooked aspect of this alignment is the perceptual alignment. Perceptual modalities like touch are more multifaceted and nuanced co
Externí odkaz:
http://arxiv.org/abs/2406.06587
Autor:
R. Pichler, A.K. Lindner, E. Compérat, P. Obrist, G. Schäfer, T. Todenhöfer, W. Horninger, C. Zoran, G. Untergasser
Publikováno v:
European Urology Open Science, Vol 19, Iss , Pp e202- (2020)
Externí odkaz:
https://doaj.org/article/cb01e048be40430f85259835b73ed04a
Autor:
Harte, Noëlle, Obrist, Dominik, Caversaccio, Marco, Lajoinie, Guillaume P. R., Wimmer, Wilhelm
The cochlea is our fluid-filled organ of hearing with a unique spiral shape. The physiological role of this shape remains unclear. Previous research has paid only little attention to the occurrence of transverse flow in the cochlea, in particular in
Externí odkaz:
http://arxiv.org/abs/2303.15603
The rise of Machine Learning (ML) is gradually digitalizing and reshaping the fashion industry. Recent years have witnessed a number of fashion AI applications, for example, virtual try-ons. Textile material identification and categorization play a c
Externí odkaz:
http://arxiv.org/abs/2301.06160
We consider estimation of undirected Gaussian graphical models and inverse covariances in high-dimensional scenarios by penalizing the corresponding precision matrix. While single $L_1$ (Graphical Lasso) and $L_2$ (Graphical Ridge) penalties for the
Externí odkaz:
http://arxiv.org/abs/2101.02148