* Jan 9: Gaussian processes - applications and computations (optimization of function) : [[http://www.math.ntnu.no/~joeid/MA8702/jan9.pdf|Lecture notes]]
  * Jan 16: Gaussian process regression and Gaussian Markov random fields : [[http://www.math.ntnu.no/~joeid/MA8702/jan16.pdf|Lecture notes]]
  * Jan 23: Latent Gaussian models, spatial Generalized linear mixed models (GLMMs) : [[http://www.math.ntnu.no/~joeid/MA8702/jan23.pdf|Lecture notes]]
  * Jan 30: Project GPs.
  * Feb 6: Integrated nested laplace approximation - INLA (fast approximate Bayesian inference, examples of GLMMs) : [[http://www.math.ntnu.no/~joeid/MA8702/feb6.pdf|Lecture notes]]
  * Feb 13: Template model builder (frequentist inference), [[http://www.math.ntnu.no/~joeid/MA8702/feb13.pdf|Lecture notes]]
  * Feb 20: Project
  * Feb 27: New Markov chain Monte Carlo (MCMC) methods : [[http://www.math.ntnu.no/~joeid/MA8702/feb27.pdf|Lecture notes]]
  * March 5: Hamiltonian Monte Carlo methods : [[http://www.math.ntnu.no/~joeid/MA8702/march5.pdf|Lecture notes]]
  * March 12: Project
  * March 19: Sequential Monte Carlo methods: particle filters, Ensemble Kalman filters. [[http://www.math.ntnu.no/~joeid/MA8702/march19.pdf|Lecture notes]]
  * March 26: Sequential Monte Carlo methods: particle filters, Ensemble Kalman filters. [[http://www.math.ntnu.no/~joeid/MA8702/march26.pdf|Lecture notes]]
  * April 2: Project. 
  * April 16: New clustering methods and dimension reduction techniques. [[http://www.math.ntnu.no/~joeid/MA8702/april16.pdf|Lecture notes]]
  * April 23: New clustering methods and dimension reduction techniques [[http://www.math.ntnu.no/~joeid/MA8702/april23.pdf|Lecture notes]]
  * April 30: Project.