Chapter 6: Gibbs Sampling - GitHub Pages

importance sampling. Markov chain Monte Carlo (MCMC) is a sampling technique that works remarkably well in many situations like this. Roughly speaking, my intuition for why MCMC often works well in practice is that (a)the region of high probability tends to be \connected", that is, you can get from one

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Kalman lter and smoother - GitHub Pages

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Kalman lter became an integral part of the Apollo navigation computer. Today, essentially all high-performance navigation systems use a Kalman lter or some variant thereof. The method is used in rockets, missiles, spacecraft including the international space station, unmanned aerial vehicles, ground robots, and recently, self-driving cars. 2 Model

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Introduction to Markov Chain Monte Carlo Monte Carlo: sample from a distribution – to estimate the distribution – to compute max, mean Markov Chain Monte Carlo: sampling using “local” information – Generic “problem solving technique” – decision/optimization/value problems – generic, but not necessarily very efficient Based on - Neal Madras: Lectures on Monte Carlo …

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