This is a python and fortran implementation of the Hidden Markov Topic model (HMTM). This is a hierarchical coupling of Hidden Markov Models. It is described in the following article.
- Andrews, M. & Vigliocco, G. (In Press) The Hidden Markov Topic Model: A Probabilistic Model of Semantic Representation. Topics in Cognitive Science. [pdf]
This is a python and fortran implementation of the Latent Dirichlet Allocation (LDA) model.
This is a python and C module that implements a type of LDA model whose latent variables simultaneously define two distributions over discrete data. This model is described in the following article, where it is referred to as the "combined model".
- Andrews, M., Vigliocco, G. & Vinson, D. (2009). Integrating Experiential and Distributional Data to Learn Semantic Representations. Psychological Review, Vol. 116(3), pp 463-498. [pdf]
It also implements the standard LDA model.