Zobrazeno 1 - 10
of 20
pro vyhledávání: '"Sambu Seo"'
Publikováno v:
IEEE Open Journal of Intelligent Transportation Systems, Vol 3, Pp 33-44 (2022)
Real-time load information in public transport is of high importance for both passengers and service providers. Neural algorithms have shown a high performance on various object counting tasks and play a continually growing methodological role in dev
Externí odkaz:
https://doaj.org/article/ed636ead0e0944d88aeb62721aa4ae9a
Publikováno v:
Addiction Biology. 20:1042-1055
In alcohol dependence, individual prediction of treatment outcome based on neuroimaging endophenotypes can help to tailor individual therapeutic offers to patients depending on their relapse risk. We built a prediction model for prospective relapse o
Autor:
Frauke Nees, Alexander Genauck, Uli Bromberg, Christian Büchel, Juliane H. Fröhner, Vincent Frouin, Herta Flor, Luise Poustka, Anne Beck, Tobias Banaschewski, Michael N. Smolka, Dimitri Papadopoulos Orfanos, Klaus Obermayer, Sarah Hohmann, Sambu Seo, Hugh Garavan, Caroline Matthis, Erin Burke Quinlan, Andreas Heinz, Penny A. Gowland, Robert Whelan, Bernd Ittermann, Henrik Walter, Jean-Luc Martinot, Sylvane Desrivières, Gunter Schumann, Arun L.W. Bokde, Marie-Laure Paillère Martinot
Publikováno v:
Addiction biology. 24(4)
Abnormalities across different domains of neuropsychological functioning may constitute a risk factor for heavy drinking during adolescence and for developing alcohol use disorders later in life. However, the exact nature of such multi‐domain risk
Publikováno v:
IJCNN
Pairwise clustering methods are able to handle relational data, in which a set of objects is described via a matrix of pairwise (dis)similarities. Using the framework of source coding, it has been shown that pairwise clustering can be considered as e
Autor:
Sambu, Seo, Johannes, Mohr, Anne, Beck, Torsten, Wüstenberg, Andreas, Heinz, Klaus, Obermayer
Publikováno v:
Addiction biology. 20(6)
In alcohol dependence, individual prediction of treatment outcome based on neuroimaging endophenotypes can help to tailor individual therapeutic offers to patients depending on their relapse risk. We built a prediction model for prospective relapse o
Autor:
Klaus Obermayer, Sambu Seo
Publikováno v:
Neural Networks. 17:1211-1229
In this contribution we present extensions of the Self Organizing Map and clustering methods for the categorization and visualization of data which are described by matrices rather than feature vectors. Rows and Columns of these matrices correspond t
Publikováno v:
IJCNN
How can we test for group differences in multidimensional input patterns, such as functional magnetic resonance imaging measurements or gene expression values? One solution is to split the available data into training and test set, and to estimate th
Autor:
Ben Eppinger, Hauke R. Heekeren, Johannes Mohr, Sambu Seo, Andreas Heinz, Klaus Obermayer, Shu-Chen Li
Publikováno v:
IJCNN
Web of Science
Web of Science
We suggest a multivariate genotype-phenotype association test for functional magnetic resonance imaging (fMRI) data. The method uses a voxel selection and ranking scheme based on iterative adaptive Lasso for defining a functional region of interest.
Publikováno v:
ICMLA
Pairwise clustering methods are able to handle relational data, in which a set of objects is described via a matrix of pairwise (dis)similarities. Here, we consider a cost function for pairwise clustering which maximizes model entropy under the const
Publikováno v:
ICMLA
In this work, a new learning paradigm called target selection is proposed, which can be used to test for associations between a single genetic variable and a multidimensional, quantitative phenotype. In target selection, the task of a learning machin