EQuS Bayesian Inference 2016
Alexei Gilchrist
In this workshop, we’ll introduce and examine the consequences of probability theory in various areas of physics. From the meaning of probabilities, to how to reason with incomplete information, model comparison, parameter estimation, and modelling with Bayesian networks. The approach will view probabilities as an extension of logic (i.e. following Laplace, Bernoulli, Cox, Jaynes, etc)
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The notes for this workshop are all as linked mindmaps accessible from this page. The maps are SVG files with embedded javascript which should enable pinch-zoom (except for Safari, grrr), or control-scroll to zoom, and click-and-drag to pan.
The notes are here:
/map/equs-bayesian-winter-2016/
N.B. the files can be quite large so please be patient.