Nikolaus Kriegeskorte
Affiliations: | National Institute of Mental Health, Bethesda, MD, United States |
Area:
object vision, IT, pattern-information analysisWebsite:
http://fim.nimh.nih.gov/people/NKGoogle:
"Nikolaus Kriegeskorte"Mean distance: 13.51 (cluster 29) | S | N | B | C | P |
Children
Sign in to add traineePrashant C. Raju | research assistant | 2017-2020 | Columbia |
Aneesh Kashalikar | research assistant | 2019-2021 | Columbia |
Baihan Lin | grad student | 2017- | Columbia |
Seyed-Mahdi Khaligh-Razavi | grad student | 2012-2014 | Cambridge |
Tal Golan | post-doc | ||
Benjamin Peters | post-doc | ||
Ruben S. van Bergen | post-doc | 2019- | Columbia |
Paul Linton | post-doc | 2022- | Zuckerman Mind Brain Behavior Institute |
Vassilis Pelekanos | post-doc | 2015-2017 | MRC CBU Cambridge |
Robert M. Mok | post-doc | 2016-2017 | |
Tim Christian Kietzmann | post-doc | 2016-2019 | Cambridge |
Heiko H Schütt | post-doc | 2018-2023 | Columbia |
Olivier Joly | research scientist | 2013-2015 | MRC-CBU |
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Publications
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Lippl S, Peters B, Kriegeskorte N. (2024) Can neural networks benefit from objectives that encourage iterative convergent computations? A case study of ResNets and object classification. Plos One. 19: e0293440 |
Peters B, DiCarlo JJ, Gureckis T, et al. (2024) How does the primate brain combine generative and discriminative computations in vision? Arxiv |
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 |
Taylor J, Kriegeskorte N. (2023) Extracting and visualizing hidden activations and computational graphs of PyTorch models with TorchLens. Scientific Reports. 13: 14375 |
Schütt HH, Kipnis AD, Diedrichsen J, et al. (2023) Statistical inference on representational geometries. Elife. 12 |
Doerig A, Sommers RP, Seeliger K, et al. (2023) The neuroconnectionist research programme. Nature Reviews. Neuroscience |
Taylor J, Kriegeskorte N. (2023) TorchLens: A Python package for extracting and visualizing hidden activations of PyTorch models. Biorxiv : the Preprint Server For Biology |
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 |
Farzmahdi A, Zarco W, Freiwald W, et al. (2023) Emergence of brain-like mirror-symmetric viewpoint tuning in convolutional neural networks. Biorxiv : the Preprint Server For Biology |
Jozwik KM, O'Keeffe J, Storrs KR, et al. (2022) Face dissimilarity judgments are predicted by representational distance in morphable and image-computable models. Proceedings of the National Academy of Sciences of the United States of America. 119: e2115047119 |