Daniel L K Yamins, PhD

Affiliations: 
Stanford University, Palo Alto, CA 
Area:
computational neuroscience, artificial intelligence, psychology, vision, audition
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Tyler Bonnen grad student Stanford
Imran Thobani 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
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