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Kamila Jozwik
Kamila Jozwik
Sir Henry Wellcome postdoctoral fellow, MIT, University of Cambridge
Verificeret mail på mit.edu
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Citeret af
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Pioneer factors in hormone-dependent cancers
KM Jozwik, JS Carroll
Nature Reviews Cancer 12 (6), 381, 2012
3052012
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
1532016
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
1282017
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
792016
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
76*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
512021
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
422020
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
202022
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
132018
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
102023
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
82022
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
62019
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
42019
Animacy Dimensions Ratings and Approach for Decorrelating Stimuli Dimensions
K Jozwik, I Charest, N Kriegeskorte, RM Cichy
22018
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
12019
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
What AI can learn from the biological brain
KM Jozwik
SCIENCE 372 (6544), 798-798, 2021
2021
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Artikler 1–17