David M. Blei

Topic Modeling Software

Our research group regularly releases code associated with our papers. We use Github organization to release it.

Please post questions, comments, and suggestions about this code to the topic models mailing list.

Link Model/Algorithm Language Author Notes

lda-c Latent Dirichlet allocation C D. Blei This implements variational inference for LDA.
class-slda Supervised topic models for classifiation C++ C. Wang Implements supervised topic models with a categorical response.
lda R package for Gibbs sampling in many models R J. Chang Implements many models and is fast . Supports LDA, RTMs (for networked documents), MMSB (for network data), and sLDA (with a continuous response).
online lda Online inference for LDA Python M. Hoffman Fits topic models to massive data. The demo downloads random Wikipedia articles and fits a topic model to them.
online hdp Online inference for the HDP Python C. Wang Fits hierarchical Dirichlet process topic models to massive data. The algorithm determines the number of topics.

tmve (online) Topic Model Visualization Engine Python A. Chaney A package for creating corpus browsers. See, for example, Wikipedia .
ctr Collaborative modeling for recommendation C++ C. Wang Implements variational inference for a collaborative topic models. These models recommend items to users based on item content and other users' ratings.
dtm Dynamic topic models and the influence model C++ S. Gerrish This implements topics that change over time and a model of how individual documents predict that change.

hdp Hierarchical Dirichlet processes C++ C. Wang Topic models where the data determine the number of topics. This implements Gibbs sampling.

ctm-c Correlated topic models C D. Blei This implements variational inference for the CTM.
diln Discrete infinite logistic normal C J. Paisley This implements the discrete infinite logistic normal, a Bayesian nonparametric topic model that finds correlated topics.

hlda Hierarchical latent Dirichlet allocation C D. Blei This implements a topic model that finds a hierarchy of topics. The structure of the hierarchy is determined by the data.
turbotopics Turbo topics Python D. Blei Turbo topics find significant multiword phrases in topics.

Link	Model/Algorithm	Language	Author	Notes
lda-c	Latent Dirichlet allocation	C	D. Blei	This implements variational inference for LDA.
class-slda	Supervised topic models for classifiation	C++	C. Wang	Implements supervised topic models with a categorical response.
lda	R package for Gibbs sampling in many models	R	J. Chang	Implements many models and is fast . Supports LDA, RTMs (for networked documents), MMSB (for network data), and sLDA (with a continuous response).
online lda	Online inference for LDA	Python	M. Hoffman	Fits topic models to massive data. The demo downloads random Wikipedia articles and fits a topic model to them.
online hdp	Online inference for the HDP	Python	C. Wang	Fits hierarchical Dirichlet process topic models to massive data. The algorithm determines the number of topics.
tmve (online)	Topic Model Visualization Engine	Python	A. Chaney	A package for creating corpus browsers. See, for example, Wikipedia .
ctr	Collaborative modeling for recommendation	C++	C. Wang	Implements variational inference for a collaborative topic models. These models recommend items to users based on item content and other users' ratings.
dtm	Dynamic topic models and the influence model	C++	S. Gerrish	This implements topics that change over time and a model of how individual documents predict that change.
hdp	Hierarchical Dirichlet processes	C++	C. Wang	Topic models where the data determine the number of topics. This implements Gibbs sampling.
ctm-c	Correlated topic models	C	D. Blei	This implements variational inference for the CTM.
diln	Discrete infinite logistic normal	C	J. Paisley	This implements the discrete infinite logistic normal, a Bayesian nonparametric topic model that finds correlated topics.
hlda	Hierarchical latent Dirichlet allocation	C	D. Blei	This implements a topic model that finds a hierarchy of topics. The structure of the hierarchy is determined by the data.
turbotopics	Turbo topics	Python	D. Blei	Turbo topics find significant multiword phrases in topics.