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Statistical Models of Visual Images
Eero Simoncelli

Mon Dec 08 03:30 PM -- 05:30 PM (PST) @ Regency E/F
Event URL: http://www.cns.nyu.edu/~eero/SLIDES/nips08-tutorial/ »

An overview of the problem of statistical image modeling, providing a set of examples from the image processing, computer vision, and computational neuroscience literatures. I'll describe the empirical observations that led to these models, and the use of these models in various applications.

Author Information

Eero Simoncelli (FlatIron Institute / New York University)

Eero P. Simoncelli received the B.S. degree in Physics in 1984 from Harvard University, studied applied mathematics at Cambridge University for a year and a half, and then received the M.S. degree in 1988 and the Ph.D. degree in 1993, both in Electrical Engineering from the Massachusetts Institute of Technology. He was an Assistant Professor in the Computer and Information Science department at the University of Pennsylvania from 1993 until 1996. He moved to New York University in September of 1996, where he is currently a Professor in Neural Science, Mathematics, and Psychology. In August 2000, he became an Associate Investigator of the Howard Hughes Medical Institute, under their new program in Computational Biology. In Fall 2020, he resigned his HHMI appointment to become the scientific director of the Center for Computational Neuroscience at the Flatiron Institute, of the Simons Foundation. His research interests span a wide range of topics in the representation and analysis of visual images, in both machine and biological systems.

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