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Machine Learning: a Probabilistic Perspective by Kevin Patrick Murphy. MIT Press, 2012. See new web page.
Written by Kevin Murphy. Last updated 16 June 2014. (Thanks to Alex Gorban for helping me with the switch to Google Sheets.) Review articles List of GM code at MLOSS Click here for a short article I wrote for the ISBA (International Society for Bayesian Analysis) Newsletter, December 2007, sumarizing some of the packages below. Click here for a more detailed discussion of some of these packages wr
Written by Kevin Murphy, 1999 Last updated: 23 October, 2002. This toolbox supports value and policy iteration for discrete MDPs, and includes some grid-world examples from the textbooks by Sutton and Barto, and Russell and Norvig. It does not implement reinforcement learning or POMDPs. For a very similar package, see INRA's matlab MDP toolbox. Download toolbox A brief introduction to MDPs, POMDPs
See also kernel-machines.org. List originally created by Vlad Magdin (UBC), 25 April 2005. Updated by Kevin Murphy, 15 December 2005.
Written by Kevin Murphy, 1998. Last updated: 8 June 2005. Distributed under the MIT License This toolbox supports inference and learning for HMMs with discrete outputs (dhmm's), Gaussian outputs (ghmm's), or mixtures of Gaussians output (mhmm's). The Gaussians can be full, diagonal, or spherical (isotropic). It also supports discrete inputs, as in a POMDP. The inference routines support filtering,
A Brief Introduction to Graphical Models and Bayesian Networks By Kevin Murphy, 1998. "Graphical models are a marriage between probability theory and graph theory. They provide a natural tool for dealing with two problems that occur throughout applied mathematics and engineering -- uncertainty and complexity -- and in particular they are playing an increasingly important role in the design and ana
BNT has moved to https://github.com/bayesnet/bnt. It is not supported or maintained.
Moved to here.
Written by Kevin Murphy, 1998. Last updated: 7 June 2004. This toolbox supports filtering, smoothing and parameter estimation (using EM) for Linear Dynamical Systems. Download toolbox What is a Kalman filter? Example of Kalman filtering and smoothing for tracking What about non-linear and non-Gaussian systems? Other software for Kalman filtering, etc. Recommended reading Functions kalman_filter ka
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