Zobrazeno 1 - 10
of 9 682
pro vyhledávání: '"Rakowski"'
Autor:
Rakowski Witold
Publikováno v:
Studia Ekonomiczne i Regionalne, Vol 15, Iss 2, Pp 131-157 (2022)
Subject and purpose of work: The subject of the research is the Silesian Voivodeship, identified with the region which, almost until the end of the 20th century, was characterized by a positive balance of population migration in interregional flows.
Externí odkaz:
https://doaj.org/article/53a9abb8414a4a0c93d7ee01f8088b5e
Publikováno v:
Educational Technology & Society, 2024 Oct 01. 27(4), 375-389.
Externí odkaz:
https://www.jstor.org/stable/48791561
Autor:
Gleason, Samuel P., Rakowski, Alexander, Ribet, Stephanie M., Zeltmann, Steven E., Savitzky, Benjamin H., Henderson, Matthew, Ciston, Jim, Ophus, Colin
Diffraction is the most common method to solve for unknown or partially known crystal structures. However, it remains a challenge to determine the crystal structure of a new material that may have nanoscale size or heterogeneities. Here we train an a
Externí odkaz:
http://arxiv.org/abs/2406.16310
Autor:
Rakowski, Alexander, Monti, Remo, Huryn, Viktoriia, Lemanczyk, Marta, Ohler, Uwe, Lippert, Christoph
With the development of high-throughput technologies, genomics datasets rapidly grow in size, including functional genomics data. This has allowed the training of large Deep Learning (DL) models to predict epigenetic readouts, such as protein binding
Externí odkaz:
http://arxiv.org/abs/2405.19057
Autor:
Rakowski Waldemar
Publikováno v:
International Journal of Applied Mathematics and Computer Science, Vol 25, Iss 4, Pp 927-941 (2015)
In the subject literature, wavelets such as the Mexican hat (the second derivative of a Gaussian) or the quadratic box spline are commonly used for the task of singularity detection. The disadvantage of the Mexican hat, however, is its unlimited supp
Externí odkaz:
https://doaj.org/article/375984425c784dc992396d18f96edf03
We consider the problem of identifying the signal shared between two one-dimensional target variables, in the presence of additional multivariate observations. Canonical Correlation Analysis (CCA)-based methods have traditionally been used to identif
Externí odkaz:
http://arxiv.org/abs/2306.15619