Bayesian Models of Perception, Cognition and Learning
Bayesian Models of Perception, Cognition and Learning
This lecture describes Bayesian memory and learning; how to go from observations to latent variables.
Topics covered in this lesson
- Bayes' rule, loss functions (i.e.,utility functions)
- Posterior mean and median, maximum a posteriori (MAP)
- Perception and likelihood ratio
- Bayesian estimation motor task, different strategies
- Combining priors and likelihood, different priors
External Links
Prerequisites
- Basic probablity theory
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