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Semantic Models for Higher-Order Bayesian Inference - Sam Staton, University of Oxford

Semantic Models for Higher-Order Bayesian Inference - Sam Staton, University of Oxford

Alan Turing Institute via YouTube Direct link

Intro

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Intro

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Classroom Contents

Semantic Models for Higher-Order Bayesian Inference - Sam Staton, University of Oxford

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  1. 1 Intro
  2. 2 A spectrum of modelling methods
  3. 3 Motivation
  4. 4 Probabilistic programming
  5. 5 Example
  6. 6 Bayesian regression
  7. 7 Semantic models
  8. 8 Synthetic measure theory
  9. 9 Random elements
  10. 10 Modular inference algorithms

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