Daniel L K Yamins, PhD

Affiliations: 
Stanford University, Palo Alto, CA 
Area:
computational neuroscience, artificial intelligence, psychology, vision, audition
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Publications

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Bonnen T, Yamins DLK, Wagner AD. (2021) When the ventral visual stream is not enough: A deep learning account of medial temporal lobe involvement in perception. Neuron
Zhuang C, Yan S, Nayebi A, et al. (2021) Unsupervised neural network models of the ventral visual stream. Proceedings of the National Academy of Sciences of the United States of America. 118
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
Yamins DL, DiCarlo JJ. (2016) Eight open questions in the computational modeling of higher sensory cortex. Current Opinion in Neurobiology. 37: 114-120
Yamins DL, DiCarlo JJ. (2016) Using goal-driven deep learning models to understand sensory cortex. Nature Neuroscience. 19: 356-65
Hong H, Yamins DL, Majaj NJ, et al. (2016) Explicit information for category-orthogonal object properties increases along the ventral stream. Nature Neuroscience
Kell A, Yamins D, Norman-Haignere S, et al. (2015) Computational similarities between visual and auditory cortex studied with convolutional neural networks, fMRI, and electrophysiology. Journal of Vision. 15: 1093
Yamins D, Cohen M, Hong H, et al. (2015) The Emergence of Face-Selective Units in a Model that Has Never Seen a Face. Journal of Vision. 15: 754
Bergstra J, Komer B, Eliasmith C, et al. (2015) Hyperopt: A Python library for model selection and hyperparameter optimization Computational Science and Discovery. 8
Afraz A, Yamins DL, DiCarlo JJ. (2014) Neural Mechanisms Underlying Visual Object Recognition. Cold Spring Harbor Symposia On Quantitative Biology. 79: 99-107
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