Pioneer factors in hormone-dependent cancers KM Jozwik, JS Carroll Nature Reviews Cancer 12 (6), 381, 2012 | 262 | 2012 |
FOXA1 directs H3K4 monomethylation at enhancers via recruitment of the methyltransferase MLL3 KM Jozwik, I Chernukhin, AA Serandour, S Nagarajan, JS Carroll Cell reports 17 (10), 2715-2723, 2016 | 131 | 2016 |
Deep Convolutional Neural Networks Outperform Feature-Based But Not Categorical Models in Explaining Object Similarity Judgments KM Jozwik, N Kriegeskorte, KR Storrs, M Mur Frontiers in psychology 8, 1726, 2017 | 94 | 2017 |
Visual features as stepping stones toward semantics: Explaining object similarity in IT and perception with non-negative least squares KM Jozwik, N Kriegeskorte, M Mur Neuropsychologia 83, 201-226, 2016 | 70 | 2016 |
The spatiotemporal neural dynamics underlying perceived similarity for real-world objects RM Cichy, N Kriegeskorte, KM Jozwik, JJF van den Bosch, I Charest NeuroImage 194, 12-24, 2019 | 55* | 2019 |
Atypical neurogenesis in induced pluripotent stem cells from autistic individuals D Adhya, V Swarup, R Nagy, L Dutan, C Shum, EP Valencia-Alarcón, ... Biological psychiatry 89 (5), 486-496, 2021 | 35 | 2021 |
Topographic deep artificial neural networks reproduce the hallmarks of the primate inferior temporal cortex face processing network H Lee, E Margalit, KM Jozwik, MA Cohen, N Kanwisher, DLK Yamins, ... bioRxiv, 2020 | 26 | 2020 |
Deep convolutional neural networks, features, and categories perform similarly at explaining primate high-level visual representations K Jozwik, N Kriegeskorte, RM Cichy, M Mur Cognitive Computational Neuroscience, 2018 | 9 | 2018 |
Face dissimilarity judgements are predicted by representational distance in morphable and image-computable models KM Jozwik*, J O'Keeffe*, KR Storrs*, W Guo, T Golan, N Kriegeskorte Proceedings of the National Academy of Sciences 119 (27), 2022 | 7 | 2022 |
To find better neural network models of human vision, find better neural network models of primate vision KM Jozwik, M Schrimpf, N Kanwisher, JJ DiCarlo BioRxiv, 688390, 2019 | 5 | 2019 |
Large-scale hyperparameter search for predicting human brain responses in the Algonauts challenge KM Jozwik, M Lee, T Marques, M Schrimpf, P Bashivan BioRxiv, 689844, 2019 | 4 | 2019 |
Disentangling five dimensions of animacy in human brain and behaviour KM Jozwik, E Najarro, JJF van den Bosch, I Charest, RM Cichy, ... Communications Biology 5 (1), 1-15, 2022 | 2 | 2022 |
Animacy Dimensions Ratings and Approach for Decorrelating Stimuli Dimensions K Jozwik, I Charest, N Kriegeskorte, RM Cichy | 2 | 2018 |
Deep neural networks and visuo-semantic models explain complementary components of human ventral-stream representational dynamics KM Jozwik, TC Kietzmann, RM Cichy, N Kriegeskorte, M Mur bioRxiv, 2021.10.25.465583v1, 2021 | 1 | 2021 |
What AI can learn from the biological brain KM Jozwik SCIENCE 372 (6544), 798-798, 2021 | | 2021 |
Face dissimilarity judgements are predicted by representational distance in morphable and image-computable models KM Jozwik, J O’Keeffe, KR Storrs, W Guo, T Golan, N Kriegeskorte bioRxiv, 2021.04. 09.438859v3, 2021 | | 2021 |
Disentangling dimensions of animacy in human brain and behaviour KM Jozwik, E Najarro, JJF Bosch, I Charest, N Kriegeskorte, RM Cichy bioRxiv, 2021.09.12.459854, 2021 | | 2021 |
Are Topographic Deep Convolutional Neural Networks Better Models of the Ventral Visual Stream? KM Jozwik, HD Lee, N Kanwisher, J DiCarlo Cognitive Computational Neuroscience, 2019 | | 2019 |