Andrew Perfors
Home
Research
People
Publications
Teaching
Resources
Blog
CV
Contact
bayesianmodeling
Representations, approximations, and limitations within a computational framework for cognitive science: Commentary on article by Tecumseh Fitch
When do memory limitations lead to regularization? An experimental and computational investigation
Uses a combination of modelling and experiments to show that memory limitations at encoding cannot lead to regularisation.
Bayesian models of cognition: What's built in after all?
Uses the Bayesian modelling framework to discuss issues of innateness a la Fodor.
Levels of explanation and the workings of science
Epistemic trust: Modeling children's reasoning about others' knowledge and intent
The learnability of abstract syntactic principles
Uses a Bayesian model of grammar induction to show that a rational learner could infer that language has hierarchical phrase structures based on typical child input.
A tutorial introduction to Bayesian models of cognitive development
Gives an intuitive intro to Bayesian models as they can be used to apply to developmental questions.
Enlightenment grows from fundamentals: Comment on Jones and Love
How recursive is language? A Bayesian exploration
Probabilistic models of cognition: Exploring representations and inductive biases
»
Cite
×