Author

Magnus Thordstein

Linköping UniversityORCID 0000-0001-6747-3687Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Research Focus:dimensionality reduction· 2 Assay:electronic health records· 2 Research Focus:benchmarking· 1 Approach:statistical model· 1

Frequent Co-Authors

Anders EklundiD· 2 shared Håkan OlaussoniD· 2 shared Mats SvantessoniD· 2 shared

Activity by Year

2021-2023 · peak 1/yr

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3 top collaborators · 3 mutual co-author links

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2 shared papersNeuroscience

Anders EklundORCID

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2 papers

Recent·Most cited

NeuroscienceBrain SciencesPeer-reviewedMar 7, 2023

Get a new perspective on EEG: Convolutional neural network encoders for parametric t-SNE.

Mats Svantesson, Håkan Olausson, Anders Eklund, Magnus Thordstein

This paper develops CNN encoders for parametric t-SNE to analyze EEG data, producing low-dimensional representations that capture EEG characteristics and generalize to new data.

15 citations

electronic health recordsdeep learning

𝕏 PostBluesky

NeuroscienceJournal of Neuroscience MethodsPeer-reviewedMar 9, 2021

Virtual EEG-electrodes: Convolutional neural networks as a method for upsampling or restoring channels

Mats Svantesson, Håkan Olausson, Anders Eklund, Magnus Thordstein

This paper uses convolutional neural networks to upsample or restore EEG channels, showing better performance than interpolation methods.

33 citations

electronic health recordsdeep learning

𝕏 PostBluesky