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 trainee| Prashant 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 |
BETA: Related publications
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Publications
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| Peters B, Blohm G, Haefner R, et al. (2024) Generative adversarial collaborations: a new model of scientific discourse. Trends in Cognitive Sciences |
| Lin B, Kriegeskorte N. (2024) The topology and geometry of neural representations. Proceedings of the National Academy of Sciences of the United States of America. 121: e2317881121 |
| Farzmahdi A, Zarco W, Freiwald WA, et al. (2024) Emergence of brain-like mirror-symmetric viewpoint tuning in convolutional neural networks. Elife. 13 |
| 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 |