| Pioneer factors in hormone-dependent cancers KM Jozwik, JS Carroll Nature Reviews Cancer 12 (6), 381, 2012 | 309 | 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 | 168 | 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 | 142 | 2017 |
| 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 | 94* | 2019 |
| 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 | 85 | 2016 |
| 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 | 60 | 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 | 55 | 2020 |
| 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 | 29 | 2022 |
| 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 Journal of Neuroscience 43 (10), 1731-1741, 2023 | 21 | 2023 |
| 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 | 20 | 2022 |
| 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 | 14 | 2018 |
| 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 | 7 | 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 |
| Animacy Dimensions Ratings and Approach for Decorrelating Stimuli Dimensions K Jozwik, I Charest, N Kriegeskorte, RM Cichy | 2 | 2018 |
| What AI can learn from the biological brain KM Jozwik SCIENCE 372 (6544), 798-798, 2021 | 1 | 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 | 1 | 2019 |
| First steps in using topographic deep artificial neural network models to generate hypotheses about not-yet-detected functional neural aggregates in the ventral stream KM Jozwik, H Lee, N Kanwisher, JJ DiCarlo Cognitive Computational Neuroscience, 2023 | | 2023 |