Feature-reweighted representational similarity analysis: A method for improving the fit between computational models, brains, and behavior by Philipp Kaniuth, Martin N. Hebart

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An Efficient Data Partitioning to Improve Classification Performance While Keeping Parameters Interpretable. by Kristjan Korjus, Martin N Hebart, Raul Vicente

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THINGSvision: A Python Toolbox for Streamlining the Extraction of Activations From Deep Neural Networks by Lukas Muttenthaler, Lukas Muttenthaler, Martin N. Hebart

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A data-driven investigation of human action representations by Diana C. Dima, Martin N. Hebart, Leyla Isik

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Breaking continuous flash suppression: A new measure of unconscious processing during interocular suppression? by Timo eStein, Timo eStein, Martin N. Hebart, Martin N. Hebart, Philipp eSterzer, Philipp eSterzer, Philipp eSterzer

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Mesolimbic confidence signals guide perceptual learning in the absence of external feedback by Matthias Guggenmos, Gregor Wilbertz, Martin N Hebart, Philipp Sterzer

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The organizational principles of de-differentiated topographic maps in somatosensory cortex by Peng Liu, Anastasia Chrysidou, Juliane Doehler, Martin N Hebart, Thomas Wolbers, Esther Kuehn

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The representational dynamics of task and object processing in humans by Martin N Hebart, Brett B Bankson, Assaf Harel, Chris I Baker, Radoslaw M Cichy

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THINGS-data, a multimodal collection of large-scale datasets for investigating object representations in human brain and behavior by Martin N Hebart, Oliver Contier, Lina Teichmann, Adam H Rockter, Charles Y Zheng, Alexis Kidder, Anna Corriveau, Maryam Vaziri-Pashkam, Chris I Baker

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