Ferenc Huszár

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A central challenge in cognitive science is to measure and quantify the mental representations humans develop – in other words, to 'read' subject's minds. In order to eliminate potential biases in reporting mental contents due to verbal elaboration, subjects' responses in experiments are often limited to binary decisions or discrete choices that do not(More)
Humans develop rich mental representations that guide their behavior in a variety of everyday tasks. However, it is unknown whether these representations, often formalized as priors in Bayesian inference, are specific for each task or subserve multiple tasks. Current approaches cannot distinguish between these two possibilities because they cannot extract(More)
b Acknowledgements I would like to thank Carl Rasmussen for advice throughout my PhD; Steven Bottone for extensive proof reading; Marc Deisenroth for assisting me in acquiring his L A T E X skills. I acknowledge my examiners Zoubin Ghahramani (internal) and Amos Storkey (external). I would like to thank my co-authors in the publications leading up to my(More)
Recently, several models based on deep neural networks have achieved great success in terms of both reconstruction accuracy and computational performance for single image super-resolution. In these methods, the low resolution (LR) input image is upscaled to the high resolution (HR) space using a single filter, commonly bicubic interpolation, before(More)
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