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Pattern inference theory: A probabilistic approach to vision

In Dieter Heyer & Rainer Mausfeld (eds.), Perception and the Physical World. Wiley. pp. 191--228 (2002)

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  1. Bayes in the Brain—On Bayesian Modelling in Neuroscience.Matteo Colombo & Peggy Seriès - 2012 - British Journal for the Philosophy of Science 63 (3):697-723.
    According to a growing trend in theoretical neuroscience, the human perceptual system is akin to a Bayesian machine. The aim of this article is to clearly articulate the claims that perception can be considered Bayesian inference and that the brain can be considered a Bayesian machine, some of the epistemological challenges to these claims; and some of the implications of these claims. We address two questions: (i) How are Bayesian models used in theoretical neuroscience? (ii) From the use of Bayesian (...)
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  • Vision as Bayesian inference: analysis by synthesis?Alan Yuille & Daniel Kersten - 2006 - Trends in Cognitive Sciences 10 (7):301-308.
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  • Bridging language with the rest of cognition: computational, algorithmic and neurobiological issues and methods.Shimon Edelman - unknown
    The computational program for theoretical neuroscience initiated by Marr and Poggio (1977) calls for a study of biological information processing on several distinct levels of abstraction. At each of these levels — computational (defining the problems and considering possible solutions), algorithmic (specifying the sequence of operations leading to a solution) and implementational — significant progress has been made in the understanding of cognition. In the past three decades, computational principles have been discovered that are common to a wide range of (...)
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