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SUMMARY:When efficient encoding meets Bayesian decoding - Alan Stocker (Un
 iversity of Pennsylvania)
DTSTART:20161216T130000Z
DTEND:20161216T140000Z
UID:TALK69124@talks.cam.ac.uk
CONTACT:John Mollon
DESCRIPTION:Bayesian inference has been a successful and principled model 
 framework for explaining perceptual behavior. However\, in many cases it h
 as been difficult to convincingly justify the choices of the model paramet
 ers (i.e. the likelihood functions and prior beliefs) needed to explain th
 e data. I will demonstrate how we used the efficient coding hypothesis to 
 derive a new and better constrained formulation of the Bayesian observer m
 odel. The new model makes a set of rather surprising and counter-intuitive
  predictions that\, however\, are supported both by neural and psychophysi
 cal data. I will discuss the general implications of the new framework for
  our understanding of perceptual behavior.
LOCATION:Kenneth Craik Room\, Craik-Marshall Building\, Downing Site
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