Perception as Bayesian Inference

By David C. Knill, W. Richards. 2008

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Visual equivalence: towards a new standard for image fidelity (2007, background): “2004], and build computational models of how vision might combine different sources [Knill and Richards 1996] to recover shape.”
Bayesian decision theory in sensorimotor control. (2006, unknown): “Bayesian integration in perception In addition to results from sensorimotor integration, other research has addressed how human perception can be described by Bayesian estimation processes ([ 16 ,17], see Yuille and Kersten, this issue).”
Noise characteristics and prior expectations in human visual speed perception (2006, methodology): “Bayesian models have also been developed to explain other aspects of human perception [ 26 ].”
The Bayesian reader: explaining word recognition as an optimal Bayesian decision process. (2006, background): “Geisler, 2003; Knill, Kersten, & Yuille, 1996), as this is the optimal way to combine perceptual information with knowledge of prior probability.”
Goal-directed decision making as probabilistic inference: a computational framework and potential neural correlates. (2012, unknown): “image) (Dayan, Hinton, & Zemel, 1995; Kersten, Mamassian, & Yuille, 2004; Knill & Richards, 1996; Yuille & Kersten, 2006).”