Implementations of various topic models written in Python. Note that some of the implementations (the models with MCMC) are extremely slow. I do not recommend to use it for large scale datasets.
- Latent Dirichlet allocation
- Collaborative topic model
- Variational inference
- Relational topic model (VI)
- Author-Topic model
- HMM-LDA
- Discrete infinite logistic normal (DILN)
- Variational inference
- Supervised topic model
- Stochastic (Gibbs) EM
- Variational inference
- Hierarchical Dirichlet process
- Collapsed Gibbs sampling
- Hierarchical Dirichlet scaling process
