ANDREA PIZZOFERRATO
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University of Bath

MA50247 Bayesian and Large Scale Methods 2020/2021


Index

  • General Informations​
  • Syllabus

General Informations

At the beginning of this unit we will look at the Stochastic Processes using the Quantum Formalism. This will allow Mathematics and Physics student to be on the same page. Then, we will look at sampling random numbers from a given probability distribution function and at some advanced MCMC methods.
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The second part of this module will be delivered by Professor Tim Rogers.

Syllabus

  • Quantum Formalism for Linear Algebra
  • Quantum Formalism for Markov Chains - part 1
  • Quantum Formalism for Markov Chains - part 2
  • Quantum Formalism for Interacting Particle Systems - part 1
  • Quantum Formalism for Interacting Particle Systems - part 2
  • Basic Generators of Random Numbers
  • Metropolis-Hastings
  • MCMC methods: Continuous MH, Block MH, Gibbs Sampler
  • Poisson Processes
  • MCMC methods: ZigZag Sampler
  • Revision of MATLAB code for the ZigZag Sampler
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