Blei Lab

causal-text-embeddings

Software and data for "Using Text Embeddings for Causal Inference"

ctr

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.

deconfounder_tutorial

dtm

This implements topics that change over time (Dynamic Topic Models) and a model of how individual documents predict that change.

edward

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

hdp

Hierarchical Dirichlet processes. Topic models where the data determine the number of topics. This implements Gibbs sampling.

lda-c

This is a C implementation of variational EM for latent Dirichlet allocation (LDA), a topic model for text or other discrete data.

online-hdp

Online inference for the Hierarchical Dirichlet Process. Fits hierarchical Dirichlet process topic models to massive data. The algorithm determines the number of topics.

onlineldavb

Online variational Bayes for latent Dirichlet allocation (LDA)

treeffuser

Treeffuser is an easy-to-use package for probabilistic prediction on tabular data with tree-based diffusion models.

blei-lab/edward

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

blei-lab/onlineldavb

Online variational Bayes for latent Dirichlet allocation (LDA)

blei-lab/dtm

This implements topics that change over time (Dynamic Topic Models) and a model of how individual documents predict that change.

blei-lab/lda-c

This is a C implementation of variational EM for latent Dirichlet allocation (LDA), a topic model for text or other discrete data.

blei-lab/hdp

Hierarchical Dirichlet processes. Topic models where the data determine the number of topics. This implements Gibbs sampling.

blei-lab/ctr

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.

blei-lab/causal-text-embeddings

Software and data for "Using Text Embeddings for Causal Inference"

blei-lab/deconfounder_tutorial

blei-lab/publications

The pdf and LaTeX for each paper (and sometimes the code and data used to generate the figures).

blei-lab/class-slda

Implements supervised topic models with a categorical response.

blei-lab/variational-smc

Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)

blei-lab/deep-exponential-families

Deep exponential families (DEFs)

blei-lab/DynamicPoissonFactorization

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.

blei-lab/turbotopics

Turbo topics find significant multiword phrases in topics.

blei-lab/ars-reparameterization

Source code for Naesseth et. al. "Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms" (2017)

blei-lab/zero-inflated-embedding

Code for the icml paper "zero inflated exponential family embedding"

blei-lab/context-selection-embedding

Context Selection for Embedding Models

blei-lab/treeffuser

Treeffuser is an easy-to-use package for probabilistic prediction on tabular data with tree-based diffusion models.

blei-lab/tmv

topic model visualization

blei-lab/deconfounder_public

blei-lab/factorial-network-models

Discussion of Durante et al for JSM 2017. Includes factorial network model generalization.

blei-lab/markovian-score-climbing

blei-lab/expo-mf

Exposure Matrix Factorization: modeling user exposure in recommendation

blei-lab/circuitry

blei-lab/poisson-influence-factorization

blei-lab/Riken_tutorial

blei-lab/treeffuser-private-dev

Development branch of Treeffuser.

blei-lab/embvis

Tool for visualizing and browsing over data point embeddings

blei-lab/ml-field-experiments

blei-lab/synthetic_controls