@blei-lab

Blei Lab

We are malleable but resistant to corrosion.

  • A library for probabilistic modeling, inference, and criticism. Deep generative models, variational inference. Runs on TensorFlow.

    Python 1,539 225 Updated Jan 22, 2017
  • Python 2 2 Updated Jan 5, 2017
  • The pdf and LaTeX for each paper (and sometimes the code and data used to generate the figures).

    TeX 25 6 Updated Dec 14, 2016
  • This implements topics that change over time (Dynamic Topic Models) and a model of how individual documents predict that change.

    Shell 33 20 Updated Oct 12, 2016
  • Online variational Bayes for latent Dirichlet allocation (LDA)

    Python 51 27 Updated Oct 11, 2016
  • This is a C implementation of variational EM for latent Dirichlet allocation (LDA), a topic model for text or other discrete data.

    C 48 38 Updated Jun 9, 2016
  • Dynamic version of Poisson Factorization (dPF). dPF captures the changing interest of users and the evolution of items over time according to user-item ratings.

    C++ 28 18 Updated Feb 22, 2016
  • Exposure Matrix Factorization: modeling user exposure in recommendation

    Jupyter Notebook 3 8 Updated Feb 15, 2016
  • Deep exponential families (DEFs)

    C++ 20 4 Updated Sep 23, 2015
  • Collaborative modeling for recommendation. Implements variational inference for a collaborative topic models. These models recommend items to users based on item content and other users' ratings.

    C++ 61 21 Updated Aug 19, 2015
  • Turbo topics find significant multiword phrases in topics.

    Python 25 7 Updated Jun 16, 2015
  • Latent Dirichlet allocation (LDA) with bumping variational inference.

    C++ 5 5 Updated Jun 8, 2015
  • create a browser of a corpus using a topic model; original TMVE implementation (static pages)

    Python 5 10 Updated May 21, 2015
  • Hierarchical Dirichlet processes. Topic models where the data determine the number of topics. This implements Gibbs sampling.

    C++ 51 18 Updated Mar 30, 2015
  • Online inference for the Hierarchical Dirichlet Process. Fits hierarchical Dirichlet process topic models to massive data. The algorithm determines the number of topics.

    Python 36 23 Updated Mar 30, 2015
  • Implements supervised topic models with a categorical response.

    C++ 19 6 Updated Mar 29, 2015
  • collaborative topic modeling

    C++ 4 13 Updated Dec 31, 2014
  • This implements the discrete infinite logistic normal, a Bayesian nonparametric topic model that finds correlated topics.

    C 2 5 Updated Oct 9, 2014
  • This implements hierarchical latent Dirichlet allocation, a topic model that finds a hierarchy of topics. The structure of the hierarchy is determined by the data.

    JavaScript 27 12 Updated Oct 5, 2014
  • This implements variational inference for the correlated topic model.

    C 5 4 Updated Oct 5, 2014
  • tmv

    Forked from ajbc/tmv

    topic model visualization

    Python 2 16 Updated Aug 26, 2014
  • The old version of the latent Dirichlet allocation package for R

    R 1 16 Updated Aug 19, 2014