Jan 9: Gaussian processes - applications and computations (optimization of function) :
Lecture notes
Jan 16: Gaussian process regression and Gaussian Markov random fields :
Lecture notes
Jan 23: Latent Gaussian models, spatial Generalized linear mixed models (GLMMs) :
Lecture notes
Jan 30: Project GPs.
Feb 6: Integrated nested laplace approximation - INLA (fast approximate Bayesian inference, examples of GLMMs) :
Lecture notes
Feb 13: Template model builder (frequentist inference),
Lecture notes
Feb 20: Project
Feb 27: New Markov chain Monte Carlo (MCMC) methods :
Lecture notes
March 5: Hamiltonian Monte Carlo methods :
Lecture notes
March 12: Project
March 19: Sequential Monte Carlo methods: particle filters, Ensemble Kalman filters.
Lecture notes
March 26: Sequential Monte Carlo methods: particle filters, Ensemble Kalman filters.
Lecture notes
April 2: Project.
April 16: New clustering methods and dimension reduction techniques.
Lecture notes
April 23: New clustering methods and dimension reduction techniques
Lecture notes
April 30: Project.