Zobrazeno 1 - 10
of 810
pro vyhledávání: '"Laubichler A"'
In this work, we introduce a generalized framework for multiscale state-space modeling that incorporates nested nonlinear dynamics, with a specific focus on Bayesian learning under switching regimes. Our framework captures the complex interactions be
Externí odkaz:
http://arxiv.org/abs/2410.19074
The ubiquity of multiscale interactions in complex systems is well-recognized, with development and heredity serving as a prime example of how processes at different temporal scales influence one another. This work introduces a novel multiscale state
Externí odkaz:
http://arxiv.org/abs/2408.06425
Autor:
Susanne Strohmaier, Manuel Pillai, Jakob Weitzer, Emilie Han, Lukas Zenk, Brenda M. Birmann, Martin Bertau, Guido Caniglia, Manfred D. Laubichler, Gerald Steiner, Eva S. Schernhammer
Publikováno v:
European Journal of Investigation in Health, Psychology and Education, Vol 14, Iss 8, Pp 2157-2174 (2024)
Considerable evidence links the “Big Five” personality traits (neuroticism, extroversion, conscientiousness, agreeableness, and openness) with depression. However, potential mediating and moderating factors are less well understood. We utilized d
Externí odkaz:
https://doaj.org/article/743e1b2b33f34c99a3bd6ee57362a068
Autor:
Angermann, Christoph, Schwab, Matthias, Haltmeier, Markus, Laubichler, Christian, Jónsson, Steinbjörn
Real-time estimation of actual object depth is an essential module for various autonomous system tasks such as 3D reconstruction, scene understanding and condition assessment. During the last decade of machine learning, extensive deployment of deep l
Externí odkaz:
http://arxiv.org/abs/2201.12170
Autor:
Wolpert, David H., Price, Michael H., Crabtree, Stefani A., Kohler, Timothy A., Jost, Jurgen, Evans, James, Stadler, Peter F., Shimao, Hajime, Laubichler, Manfred D.
Historical processes manifest remarkable diversity. Nevertheless, scholars have long attempted to identify patterns and categorize historical actors and influences with some success. A stochastic process framework provides a structured approach for t
Externí odkaz:
http://arxiv.org/abs/2112.05876
Autor:
David H. Wolpert, Michael H. Price, Stefani A. Crabtree, Timothy A. Kohler, Jürgen Jost, James Evans, Peter F. Stadler, Hajime Shimao, Manfred D. Laubichler
Publikováno v:
Journal of Computer Applications in Archaeology, Vol 7, Iss 1, Pp 244–245-244–245 (2024)
This article details a correction to: Wolpert, D.H., Price, M.H., Crabtree, S.A., Kohler, T.A., Jost, J., Evans, J., Stadler, P.F., Shimao, H. and Laubichler, M.D. (2024) ‘The Past as a Stochastic Process’, Journal of Computer Applications in Arc
Externí odkaz:
https://doaj.org/article/6b96ff60cdb440efafc71dedde0f4eda
Autor:
Angermann, Christoph, Moravová, Adéla, Haltmeier, Markus, Jónsson, Steinbjörn, Laubichler, Christian
Real-time estimation of actual environment depth is an essential module for various autonomous system tasks such as localization, obstacle detection and pose estimation. During the last decade of machine learning, extensive deployment of deep learnin
Externí odkaz:
http://arxiv.org/abs/2103.16938
Autor:
Angermann, Christoph, Haltmeier, Markus, Laubichler, Christian, Jónsson, Steinbjörn, Schwab, Matthias, Moravová, Adéla, Kiesling, Constantin, Kober, Martin, Fimml, Wolfgang
State-of-the-art methods for quantifying wear in cylinder liners of large internal combustion engines require disassembly and cutting of the liner. This is followed by laboratory-based high-resolution microscopic surface depth measurement that quanti
Externí odkaz:
http://arxiv.org/abs/2103.08482
Autor:
Jürgen Jost, Roberto Lalli, Manfred D. Laubichler, Eckehard Olbrich, Jürgen Renn, Guillermo Restrepo, Peter F. Stadler, Dirk Wintergrün
Publikováno v:
Journal of Social Computing, Vol 4, Iss 3, Pp 232-242 (2023)
We propose a program for a computational analysis, based on large scale datasets, of deep conceptual and formal structures, representing the mechanisms of historical transformations in different domains ranging from biological to social, cultural, an
Externí odkaz:
https://doaj.org/article/cb93cf7e7fc849f7a440b3f6bf4bc1d6
Autor:
Stephanie Pfirman, Manfred Laubichler
Publikováno v:
Quantitative Science Studies, Vol 4, Iss 4 (2024)
Externí odkaz:
https://doaj.org/article/bb5483ff5bf5477aa7558bd8d63bca9f