http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
Bayesian models of perception and action
1 online resource ( xiii, 382 pages) : illustrations (some color).
Uncertainty and Inference -- Using Bayes' Rule -- Bayesian Inference under Measurement Noise -- The Response Distribution -- Cue Combination and Evidence Accumulation -- Learning as Inference -- Discrimination and Detection -- Binary Classification -- Top-Level Nuisance Variables and Ambiguity -- Same-Different Judgment - Search -- Inference in a Changing World -- Combining Inference with Utility -- The Neural Likelihood Function -- Bayesian Models in Context -- Notation -- Basics of Probability Theory -- Model Fitting and Model Comparison.
Wei Ji Ma, Konrad Paul Kording, and Daniel Goldreich.
Includes bibliographical references and index.
Cambridge, Massachusetts : MIT Press, [2023]