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
  • Collapsed Gibbs sampling
  • Variational inference
• Correlated topic Model
  • Variational inference
• Relational topic model (VI)
  • Exponential link function
• Author-Topic model
• HMM-LDA
• Discrete infinite logistic normal (DILN)
  • Variational inference
• Supervised topic model
  • Variational inference
  • Stochastic (Gibbs) EM
• Hierarchical Dirichlet process
  • Collapsed Gibbs sampling
• Hierarchical Dirichlet scaling process