@blei-lab

Blei Lab

We are malleable but resistant to corrosion.

Pinned repositories

  1. edward

    A probabilistic programming language in TensorFlow. Deep generative models, variational inference.

    Jupyter Notebook 3.8k 676

  • A probabilistic programming language in TensorFlow. Deep generative models, variational inference.

    Jupyter Notebook 3,773 676 Updated Jul 26, 2018
  • Implements supervised topic models with a categorical response.

    C++ 38 13 GPL-2.0 Updated Jun 26, 2018
  • Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)

    Python 7 2 MIT Updated Feb 27, 2018
  • Deep exponential families (DEFs)

    C++ 39 10 Updated Feb 8, 2018
  • This implements topics that change over time (Dynamic Topic Models) and a model of how individual documents predict that change.

    Shell 94 51 GPL-2.0 Updated Dec 12, 2017
  • Context Selection for Embedding Models

    Python 17 8 Updated Nov 2, 2017
  • Code for the icml paper "zero inflated exponential family embedding"

    Python 15 4 Updated Nov 2, 2017
  • Discussion of Durante et al for JSM 2017. Includes factorial network model generalization.

    Jupyter Notebook 6 1 Updated Aug 14, 2017
  • The pdf and LaTeX for each paper (and sometimes the code and data used to generate the figures).

    TeX 62 11 Updated Apr 25, 2017
  • Source code for Naesseth et. al. "Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms" (2017)

    Jupyter Notebook 10 2 MIT Updated Apr 25, 2017
  • tmv

    Forked from ajbc/tmv

    topic model visualization

    Python 13 23 GPL-3.0 Updated Mar 31, 2017
  • Jupyter Notebook 4 Updated Mar 8, 2017
  • Hierarchical Dirichlet processes. Topic models where the data determine the number of topics. This implements Gibbs sampling.

    C++ 107 42 GPL-2.0 Updated Feb 22, 2017
  • Online variational Bayes for latent Dirichlet allocation (LDA)

    Python 123 50 GPL-3.0 Updated Oct 12, 2016
  • This is a C implementation of variational EM for latent Dirichlet allocation (LDA), a topic model for text or other discrete data.

    C 110 75 LGPL-2.1 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++ 36 25 GPL-3.0 Updated Feb 22, 2016
  • Exposure Matrix Factorization: modeling user exposure in recommendation

    Jupyter Notebook 4 24 Updated Feb 15, 2016
  • 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++ 115 39 GPL-2.0 Updated Aug 19, 2015
  • Turbo topics find significant multiword phrases in topics.

    Python 35 10 Updated Jun 16, 2015
  • Latent Dirichlet allocation (LDA) with bumping variational inference.

    C++ 8 5 GPL-2.0 Updated Jun 8, 2015
  • create a browser of a corpus using a topic model; original TMVE implementation (static pages)

    Python 6 13 Updated May 21, 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 83 44 GPL-2.0 Updated Mar 30, 2015
  • collaborative topic modeling

    C++ 9 22 GPL-3.0 Updated Dec 31, 2014
  • This implements the discrete infinite logistic normal, a Bayesian nonparametric topic model that finds correlated topics.

    C 4 3 LGPL-2.1 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 51 18 Updated Oct 5, 2014
  • This implements variational inference for the correlated topic model.

    C 14 6 Updated Oct 5, 2014
  • The old version of the latent Dirichlet allocation package for R

    R 2 17 Updated Aug 18, 2014