Daniel L K Yamins, PhD
Affiliations: | Stanford University, Palo Alto, CA |
Area:
computational neuroscience, artificial intelligence, psychology, vision, auditionGoogle:
"Daniel Yamins"Mean distance: 14.62
Children
Sign in to add trainee| Tyler Bonnen | grad student | Stanford | |
| Aran Nayebi | grad student | 2016-2022 | Stanford |
| Daniel M. Bear | post-doc | 2017- | Stanford |
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Publications
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| Richards BA, Lillicrap TP, Beaudoin P, et al. (2019) A deep learning framework for neuroscience. Nature Neuroscience. 22: 1761-1770 |
| Zhuang C, Yamins D. (2018) Using multiple optimization tasks to improve deep neural network models of higher ventral cortex Journal of Vision. 18: 905 |
| Margalit E, Lee H, DiCarlo J, et al. (2018) Pinwheel-like Iso-Orientation Domains in a Convolutional Neural Network Model Journal of Vision. 18: 771 |
| Wammes J, Fan J, Lee R, et al. (2018) Changing object representations during visual production training Journal of Vision. 18: 763 |
| Nayebi A, Kubilius J, Bear D, et al. (2018) Convolutional recurrent neural network models of dynamics in higher visual cortex Journal of Vision. 18: 717 |
| Haber N, Mrowca D, Fei-Fei L, et al. (2018) Modeling the scientist in the crib Journal of Vision. 18: 10 |
| Zhuang C, Wang Y, Yamins D, et al. (2017) Deep Learning Predicts Correlation between a Functional Signature of Higher Visual Areas and Sparse Firing of Neurons. Frontiers in Computational Neuroscience. 11: 100 |
| Fan J, Yamins D, Turk-Browne N. (2017) Visual production induces categorical perception Journal of Vision. 17: 992 |
| Tian M, Yamins D, Grill-Spector K. (2016) Learning the 3-D structure of objects from 2-D views depends on shape, not format. Journal of Vision. 16: 7 |
| Yamins DL, DiCarlo JJ. (2016) Eight open questions in the computational modeling of higher sensory cortex. Current Opinion in Neurobiology. 37: 114-120 |