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pro vyhledávání: '"Nielsen, Søren F."'
Autor:
Jørgensen, Philip J. H.1 (AUTHOR) jehi@dtu.dk, Nielsen, Søren F.1 (AUTHOR) mnsc@dtu.dk, Hinrich, Jesper L.1 (AUTHOR) kristofferm@drcmr.dk, Schmidt, Mikkel N.1 (AUTHOR), Madsen, Kristoffer H.1,2 (AUTHOR), Mørup, Morten1 (AUTHOR) mmor@dtu.dk
Publikováno v:
Entropy. Aug2024, Vol. 26 Issue 8, p697. 24p.
Autor:
Jørgensen, Philip J. H., Nielsen, Søren F. V., Hinrich, Jesper L., Schmidt, Mikkel N., Madsen, Kristoffer H., Mørup, Morten
The PARAFAC2 is a multimodal factor analysis model suitable for analyzing multi-way data when one of the modes has incomparable observation units, for example because of differences in signal sampling or batch sizes. A fully probabilistic treatment o
Externí odkaz:
http://arxiv.org/abs/1806.08195
Autor:
Hinrich, Jesper L., Nielsen, Søren F. V., Riis, Nicolai A. B., Eriksen, Casper T., Frøsig, Jacob, Kristensen, Marco D. F., Schmidt, Mikkel N., Madsen, Kristoffer H., Mørup, Morten
Many data-driven approaches exist to extract neural representations of functional magnetic resonance imaging (fMRI) data, but most of them lack a proper probabilistic formulation. We propose a group level scalable probabilistic sparse factor analysis
Externí odkaz:
http://arxiv.org/abs/1612.04555
Dynamic functional connectivity (FC) has in recent years become a topic of interest in the neuroimaging community. Several models and methods exist for both functional magnetic resonance imaging (fMRI) and electroencephalography (EEG), and the result
Externí odkaz:
http://arxiv.org/abs/1601.00496
Akademický článek
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Autor:
Nielsen, Søren F. V., Madsen, Kristoffer H., Vinberg, Maj, Kessing, Lars V., Siebner, Hartwig R., Miskowiak, Kamilla W.
Publikováno v:
Frontiers in Neuroscience; Jul2015, p1-11, 11p, 3 Charts, 3 Graphs
Autor:
Philip Johan Havemann Jørgensen, Nielsen, Søren F. V., Jesper Løve Hinrich, Mikkel N. Schmidt, Kristoffer Hougaard Madsen, Morten Mørup
Publikováno v:
Technical University of Denmark Orbit
Jørgensen, P J H, Nielsen, S F V, Hinrich, J L, Schmidt, M N, Madsen, K H & Mørup, M 2019, Analysis of Chromatographic Data using the Probabilistic PARAFAC2 . in Proceedings of Second Workshop on Machine Learning and the Physical Sciences . 33rd Conference on Neural Information Processing Systems, Vancouver, Canada, 08/12/2019 .
Jørgensen, P J H, Nielsen, S F V, Hinrich, J L, Schmidt, M N, Madsen, K H & Mørup, M 2019, Analysis of Chromatographic Data using the Probabilistic PARAFAC2 . in Proceedings of Second Workshop on Machine Learning and the Physical Sciences . 33rd Conference on Neural Information Processing Systems, Vancouver, Canada, 08/12/2019 .
PARAFAC2 is a widely applicable method often used for analyzing multi-way chromatographic data. We recently proposed a probabilistic framework for PARAFAC2[1]. The probabilistic formulations allow for a principled way of determining the number of lat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::301969dae0ca29f880cf3017470e1d9b
https://orbit.dtu.dk/en/publications/622f32f8-71d7-4953-98b0-996bf650d1e0
https://orbit.dtu.dk/en/publications/622f32f8-71d7-4953-98b0-996bf650d1e0