Dynamic Bayesian network


Dynamic Bayesian network

A dynamic Bayesian network is a Bayesian network that represents sequences of variables. These sequences are often time-series (for example, in speech recognition) or sequences of symbols (for example, protein sequences). The hidden Markov model can be considered as a simple dynamic Bayesian network.

See also

Recursive Bayesian estimation

References

  • [1] Friedman, N., Murphy, K., and Russell, S. (1998). Learning the structure of dynamic probabilistic networks. In UAI’98, pages 139–147. Morgan Kaufmann.


Software

  • [2] The BNT toolbox by Kevin Murphy
  • [3] DBmcmc - Inferring Dynamic Bayesian Networks with MCMC
  • [4] GlobalMIT Matlab toolbox - Modeling gene regulatory network via global optimization of dynamic bayesian network