University of Bath

MA50247 Bayesian and Large Scale Methods 2021/2022

Index

General Information

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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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
  • MCMC methods: Bouncy Particle Sampler
  • MCMC methods: Skipping Sampler
  • Applications of the Skipping Sampler to power plants.
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