Johannes Mehrer

@epfl.ch

Postdoctoral researcher, Department of Life Science and School of Computer Science

Johannes Mehrer


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https://researchid.co/johannesmehrer

RESEARCH, TEACHING, or OTHER INTERESTS

Cognitive Neuroscience, Artificial Intelligence, Biological Psychiatry
833

Scholar Citations

6

Scholar h-index

6

Scholar i10-index

RECENT SCHOLAR PUBLICATIONS

  • Inducing Dyslexia in Vision Language Models
    M Honarmand, A Sharma, B AlKhamissi, J Mehrer, M Schrimpf
    ICLR 2026 (arXiv:2509.24597) , 2026
    2026.0
    Citations: 3
  • Model-Guided Microstimulation Steers Primate Visual Behavior
    J Mehrer, B Lonnqvist, A Mitola, A Gokce, P Papale, M Schrimpf
    ICLR 2026 (arXiv:2510.03684) , 2026
    2026.0
    Citations: 1
  • TopoLM: brain-like spatio-functional organization in a topographic language model
    N Rathi, J Mehrer, B AlKhamissi, T Binhuraib, NM Blauch, M Schrimpf
    ICLR 2025 (oral; arXiv:2410.11516) , 2024
    2024.0
    Citations: 12
  • Dreaming Out Loud: A Self-Synthesis Approach For Training Vision-Language Models With Developmentally Plausible Data
    B AlKhamissi, Y Tang, A Gokce, J Mehrer, M Schrimpf
    https://doi.org/10.48550/arXiv.2411.00828 , 2024
    2024.0
    Citations: 2
  • 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
    2021.0
    Citations: 169
  • 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
    2021.0
    Citations: 225
  • Individual differences among deep neural network models
    J Mehrer, CJ Spoerer, TC Kriegeskorte, Nikolaus, Kietzmann
    Nature Communications 11 , 2020
    2020.0
    Citations: 239
  • 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
    2020.0
    Citations: 165
  • Computational models of the human visual cortex: on individual differences and ecologically valid input statistics
    J Mehrer
    2020.0
  • 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
    2019.0
  • 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
    2018.0
    Citations: 12
  • 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
    2017.0
    Citations: 5
  • 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

MOST CITED SCHOLAR PUBLICATIONS

  • Individual differences among deep neural network models
    J Mehrer, CJ Spoerer, TC Kriegeskorte, Nikolaus, Kietzmann
    Nature Communications 11 , 2020
    2020.0
    Citations: 239
  • 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
    2021.0
    Citations: 225
  • 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
    2021.0
    Citations: 169
  • 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
    2020.0
    Citations: 165
  • TopoLM: brain-like spatio-functional organization in a topographic language model
    N Rathi, J Mehrer, B AlKhamissi, T Binhuraib, NM Blauch, M Schrimpf
    ICLR 2025 (oral; arXiv:2410.11516) , 2024
    2024.0
    Citations: 12
  • 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
    2018.0
    Citations: 12
  • 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
    2017.0
    Citations: 5
  • Inducing Dyslexia in Vision Language Models
    M Honarmand, A Sharma, B AlKhamissi, J Mehrer, M Schrimpf
    ICLR 2026 (arXiv:2509.24597) , 2026
    2026.0
    Citations: 3
  • Dreaming Out Loud: A Self-Synthesis Approach For Training Vision-Language Models With Developmentally Plausible Data
    B AlKhamissi, Y Tang, A Gokce, J Mehrer, M Schrimpf
    https://doi.org/10.48550/arXiv.2411.00828 , 2024
    2024.0
    Citations: 2
  • Model-Guided Microstimulation Steers Primate Visual Behavior
    J Mehrer, B Lonnqvist, A Mitola, A Gokce, P Papale, M Schrimpf
    ICLR 2026 (arXiv:2510.03684) , 2026
    2026.0
    Citations: 1
  • Computational models of the human visual cortex: on individual differences and ecologically valid input statistics
    J Mehrer
    2020.0
  • 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
    2019.0
  • 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