Tim Christian Kietzmann
Affiliations: | 2009-2016 | Institute of Cognitive Science | University of Osnabrueck |
| 2016-2019 | MRC Cognition and Brain Sciences Unit | University of Cambridge, Cambridge, England, United Kingdom |
Area:
vision, object recognition, visual attention, visual representations, awareness, machine learningWebsite:
http://www.timkietzmann.deGoogle:
"Tim Kietzmann"Mean distance: 13.52 (cluster 29) | S | N | B | C | P |
Parents
Sign in to add mentor| Peter König | grad student | Institute of Cognitive Science, University of Osnabrueck | |
| Frank Tong | grad student | Vanderbilt | |
| Nikolaus Kriegeskorte | post-doc | 2016-2019 | Cambridge |
Collaborators
Sign in to add collaborator| Niklas Wilming | collaborator | Institute of Cognitive Science, University of Osnabrueck | |
| Merav Ahissar | collaborator | 2008-2009 | Hebrew University |
| Stephan Geuter | collaborator | 2008-2010 | Institute of Cognitive Science, University of Osnabrueck |
BETA: Related publications
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Publications
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| Golan T, Taylor J, Schütt H, et al. (2023) Deep neural networks are not a single hypothesis but a language for expressing computational hypotheses. The Behavioral and Brain Sciences. 46: e392 |
| Karapetian A, Boyanova A, Pandaram M, et al. (2023) Empirically Identifying and Computationally Modelling the Brain-Behavior Relationship for Human Scene Categorization. Journal of Cognitive Neuroscience. 1-19 |
| Doerig A, Sommers RP, Seeliger K, et al. (2023) The neuroconnectionist research programme. Nature Reviews. Neuroscience |
| Jozwik KM, Kietzmann TC, Cichy RM, et al. (2023) Deep neural networks and visuo-semantic models explain complementary components of human ventral-stream representational dynamics. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience |
| Gert AL, Ehinger BV, Timm S, et al. (2022) WildLab: A naturalistic free viewing experiment reveals previously unknown EEG signatures of face processing. The European Journal of Neuroscience |
| Storrs KR, Kietzmann TC, Walther A, et al. (2021) Diverse Deep Neural Networks All Predict Human IT Well, After Training and Fitting. Journal of Cognitive Neuroscience. 1-21 |
| Mehrer J, Spoerer CJ, Jones EC, et al. (2021) An ecologically motivated image dataset for deep learning yields better models of human vision. Proceedings of the National Academy of Sciences of the United States of America. 118 |
| Mehrer J, Spoerer CJ, Kriegeskorte N, et al. (2020) Individual differences among deep neural network models. Nature Communications. 11: 5725 |
| Spoerer CJ, Kietzmann TC, Mehrer J, et al. (2020) Recurrent neural networks can explain flexible trading of speed and accuracy in biological vision. Plos Computational Biology. 16: e1008215 |
| Kietzmann J, Lee LW, McCarthy IP, et al. (2020) Deepfakes: Trick or treat? Business Horizons. 63: 135-146 |