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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
• Collaborative 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
  • Stochastic (Gibbs) EM
  • Variational inference
• Hierarchical Dirichlet process
  • Collapsed Gibbs sampling
• Hierarchical Dirichlet scaling process