- PyProbML, code to support v2 of my textbook (WIP).

- Matlab tutorial
- PMTK: probabilistic modeling toolkit
- Code written by Mark Schmidt, for optimization, structure learning, inference in UGMs, and much more!
- UGM structure learning using group L1 regularization, supports MRFs, CRFs, etc.
- DAG structure learning using L1 regularization . Uses L1 to detect Markov blankets. Can optionally perform local search over node orderings.
- Bayesian DAG learning, Bayesian inference for directed acyclic graph structures using MCMC and dynamic programming
- GMMVBEM: Variational Bayesian EM for Gaussian mixture models
- aCGH: array CGH analysis of single and multiple samples using HMMs
- MATBUGS: matlab interface to WinBUGS
- Bayes Net Toolbox: state and parameter estimation (inference and learning) for (directed) graphical models
- CRF toolbox: inference and learning in conditional random fields Contains code for loopy belief propagation and MRFs.
- HMM toolbox: inference and learning in hidden Markov models
- Kalman filter toolbox: inference and learning in linear dynamical systems
- MDP toolbox: value and policy iteration for tabular Markov decision processes
- Graph visualization: automatic layout of graphs (interface to GraphViz)
- KPMtools: miscellaneous functions, needed by many of my toolboxes.
- KPMstats: statistics functions for learning/sampling Gaussians/ multnomials, cluster weighted regression, etc.
- Graph theory toolbox: simple graph algorithms like depth first search, triangulation, etc.
- Fitting HMMs using Entropic priors, based on Matt Brand's code.
- readMNIST.m,
to parse
the MNIST digit set
file format.

- blockmatrix class
- classSchedule.m, a handy Matlab script to make web page timetables for classes. Sample output.
- Datasets in Matlab format

- Google analytics.
- Graphical models, junction tree inference for discrete graphical models (directed and undirected) in SML/NJ. (This is about 100 times faster than BNT.) Written by Clint Morgan for a project in my class, Fall 2004. Click here for his report.
- Comparison of programming languages.
- Comparison of software for graphical models