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Communicated by Terrence Sanger Statistically EfŽcient Estimation Using Population Coding Alexandre Pouget Georgetown Institute for Computational and Cognitive Sciences, Georgetown University, Washington, DC
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Document Date: 2004-01-29 12:39:36

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File Size: 1,08 MB

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City

Washington / DC / La Jolla / Los Angeles / /

Company

Wilson / /

Facility

U.S.A. Sophie Deneve Georgetown Institute / Massachusetts Institute of Technology / Georgetown University / Salk Institute / University of California at Los Angeles / Terrence Sanger Statistically EfŽcient Estimation Using Population Coding Alexandre Pouget Georgetown Institute / N stable / U.S.A. Kechen Zhang Computational Neurobiology Laboratory / /

IndustryTerm

performance comparison between various network / analytical solution / biological networks / linear and nonlinear networks / recurrent network / nonlinear recurrent network / linear network / line attractor networks / linear recurrent networks / nonlinear network / line attractor network / /

Organization

Terrence Sanger Statistically EfŽcient Estimation Using Population Coding Alexandre Pouget Georgetown Institute for Computational and Cognitive Sciences / Georgetown University / Washington / U.S.A. Sophie Deneve Georgetown Institute for Computational and Cognitive Sciences / U.S.A. Peter E. Latham Department of Neurobiology / U.S.A. Kechen Zhang Computational Neurobiology Laboratory / Salk Institute / Massachusetts Institute of Technology / University of California at Los Angeles / /

Person

Kechen Zhang / Van Essen / Peter E. Latham / Alexandre Pouget / Sophie Deneve / Duda / E. Latham Activity / /

Position

Fisher / /

ProgrammingLanguage

DC / C / ML / /

ProvinceOrState

California / Massachusetts / /

Technology

1998 Massachusetts Institute of Technology / Simulation / /

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