Non-linear shrinking of linear model errors von Helin, Runar, Indahl, Ulf, Tomic, Oliver, Liland, Kristian Hovde

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Non-linear shrinking of linear model errors von Helin, Runar, Indahl, Ulf Geir, Tomic, Oliver, Liland, Kristian Hovde

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On the possible benefits of deep learning for spectral preprocessing von Helin, Runar, Indahl, Ulf Geir, Tomic, Oliver, Liland, Kristian Hovde

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Exploring the transition from traditional data analysis to machine- and deep learning approaches von Helin, Runar

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Exploring the transition from traditional data analysis to machine- and deep learning approaches von Helin, Runar

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Existence and detectability of very fast oscillations in spiking network models von Helin, Runar

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Ranking Feature-Block Importance in Artificial Multiblock Neural Networks von Jenul, Anna, Schrunner, Stefan, Huynh, Bao Ngoc, Helin, Runar, Futsæther, Cecilia Marie, Liland, Kristian Hovde, Tomic, Oliver

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Non-linear shrinking of linear model errors von Helin, Runar, Indahl, Ulf Geir, Tomic, Oliver, Liland, Kristian Hovde

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Existence and detectability of very fast oscillations in spiking network models von Helin, Runar

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Explore the effect of data augmentation of spectroscopic data for deep learning models von Naveed, Talha

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Ranking Feature-Block Importance in Artificial Multiblock Neural Networks von Jenul, Anna, Schrunner, Stefan, Huynh, Bao Ngoc, Helin, Runar, Futsæther, Cecilia Marie, Kristian Hovde Liland, Tomic, Oliver

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