Johannes Mehrer
Johannes Mehrer
EPFL, CH, previously MRC CBU, Cambridge, UK
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Individual differences among deep neural network models
J Mehrer, CJ Spoerer, TC Kriegeskorte, Nikolaus, Kietzmann
Nature Communications 11, 2020
An ecologically motivated image dataset for deep learning yields better models of human vision
J Mehrer, CJ Spoerer, EC Jones, N Kriegeskorte, TC Kietzmann
Proceedings of the National Academy of Sciences 118 (8), e2011417118, 2021
Diverse Deep Neural Networks All Predict Human Inferior Temporal Cortex Well, After Training and Fitting
KR Storrs, TC Kietzmann, A Walther, J Mehrer, N Kriegeskorte
Journal of Cognitive Neuroscience 33 (10), 2044-2064, 2021
Recurrent neural networks can explain flexible trading of speed and accuracy in biological vision
CJ Spoerer, TC Kietzmann, J Mehrer, I Charest, N Kriegeskorte
PLOS Computational Biology 16 (10), e1008215, 2020
Deep neural networks trained with heavier data augmentation learn features closer to representations in hIT
A Hernández-García, J Mehrer, N Kriegeskorte, P König, TC Kietzmann
Conference on Cognitive Computational Neuroscience, 2018
Architecture matters: How well neural networks explain it representation does not depend on depth and performance alone
K Storrs, J Mehrer, A Walther, N Kriegeskorte
Conference on Cognitive Computational Neuroscience (CCN), 2017
Computational models of the human visual cortex: on individual differences and ecologically valid input statistics
J Mehrer
University of Cambridge, 2020
Architecture Matters: Training and Structure Both Affect How Well Deep Networks Predict Cortical Representations of Objects, Places and Faces
K Storrs, J Mehrer, A Walther, N Kriegeskorte
PERCEPTION 48, 198-198, 2019
Mokset: A shared stimulus set for ob ect vision research
SR Mok, J Mehrer, N Kriegeskorte
Modelling Human Visual Uncertainty using Bayesian Deep Neural Networks
P McClure, TC Kietzmann, J Mehrer, N Kriegeskorte
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