Biblio
Filters: Author is Poggio, T. [Clear All Filters]
Eccentricity Dependent Deep Neural Networks for Modeling Human Vision. Vision Sciences Society.
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2017. Eccentricity Dependent Deep Neural Networks: Modeling Invariance in Human Vision. AAAI Spring Symposium Series, Science of Intelligence.
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2017. On the Human Visual System Invariance to Translation and Scale. Vision Sciences Society.
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2017. Is the Human Visual System Invariant to Translation and Scale? AAAI Spring Symposium Series, Science of Intelligence.
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2017. Invariant Recognition Predicts Tuning of Neurons in Sensory Cortex. Computational and Cognitive Neuroscience of Vision. :85-104.
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2017. View-tolerant face recognition and Hebbian learning imply mirror-symmetric neural tuning to head orientation. Current Biology. 27:1-6.
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2017. Why and when can deep-but not shallow-networks avoid the curse of dimensionality: A review. International Journal of Automation and Computing. :1-17.
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Deep Learning: Mathematics and Neuroscience. A Sponsored Supplement to Science. Brain-Inspired intelligent robotics: The intersection of robotics and neuroscience:9-12.
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2016. How Important Is Weight Symmetry in Backpropagation? Thirtieth AAAI Conference on Artificial Intelligence (AAAI-16).
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“The Invariance Hypothesis Implies Domain-Specific Regions in Visual Cortex”. PLOS Computational Biology, . 11
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