Alternatives and similar repositories for publications:

Users that are interested in publications are comparing it to the libraries listed below

• blei-lab / hdp
  Hierarchical Dirichlet processes. Topic models where the data determine the number of topics. This implements Gibbs sampling.
  ☆149Updated 8 years ago
• blei-lab / class-slda
  Implements supervised topic models with a categorical response.
  ☆64Updated 3 years ago
• blei-lab / deep-exponential-families
  Deep exponential families (DEFs)
  ☆55Updated 7 years ago
• blei-lab / DynamicPoissonFactorization
  Dynamic version of Poisson Factorization (dPF). dPF captures the changing interest of users and the evolution of items over time accordin…
  ☆48Updated 9 years ago
• edwardlib / papers
  Edward content including papers, posters, and talks
  ☆91Updated 4 years ago
• kzhai / PyNPB
  Non-parametric Bayesian in Python, including Indian buffet process (IBP), hierarchical Dirichlet process (HDP).
  ☆73Updated 9 years ago
• tbroderick / streaming_vb
  This is code associated with the paper: Broderick, T, Boyd, N, Wibisono, A, Wilson, AC, and Jordan, MI. Streaming variational Bayes. Neur…
  ☆41Updated 10 years ago
• mariru / exponential_family_embeddings
  Bernoulli Embeddings for Text
  ☆83Updated 7 years ago
• wbuntine / topic-models
  Topic modelling software using non-parametric methods
  ☆70Updated 8 years ago
• dongwookim-ml / topic-model-lecture-note
  lecture notes for probabilistic topic models using ipython notebook
  ☆22Updated 10 years ago
• pmineiro / randembed
  Randomized embeddings for extreme learning
  ☆24Updated 9 years ago
• ajbc / spf
  Social Poisson Factorization
  ☆26Updated 6 years ago
• premgopalan / hgaprec
  Scalable Recommendation with Hierarchical Poisson Factorization P Gopalan, JM Hofman, DM Blei UAI, 326-335
  ☆55Updated 9 years ago
• lmjohns3 / downhill
  Stochastic gradient routines for Theano
  ☆102Updated 6 years ago
• tbroderick / bnp_tutorial
  ☆30Updated 7 years ago
• blei-lab / online-hdp
  Online inference for the Hierarchical Dirichlet Process. Fits hierarchical Dirichlet process topic models to massive data. The algorithm …
  ☆145Updated 10 years ago
• blei-lab / ctm-c
  This implements variational inference for the correlated topic model.
  ☆21Updated 10 years ago
• echen / dirichlet-process
  Introduction to Nonparametric Bayes, Infinite Mixture Models, and the Dirichlet Process (+ McDonald's)
  ☆304Updated 10 years ago
• jacobeisenstein / SAGE
  Sparse Additive Generative Model of Text
  ☆87Updated 8 years ago
• aschein / bptf
  Bayesian Poisson tensor factorization
  ☆58Updated 6 months ago
• aschein / pgds
  Poisson-Gamma dynamical systems
  ☆17Updated 8 years ago
• dallascard / neural_topic_models
  Code to accompany "A Neural Framework for Generalized Topic Models"
  ☆67Updated 6 years ago
• premgopalan / svinet
  Efficient discovery of overlapping communities in massive networks PK Gopalan, DM Blei Proceedings of the National Academy of Sciences 11…
  ☆74Updated 4 years ago
• mariru / structured_embeddings
  ☆53Updated 7 years ago
• TaddyLab / deepir
  deep inverse regression
  ☆31Updated 9 years ago
• dillonalaird / pysvihmm
  Implementation of stochastic variational inference for Bayesian hidden Markov models.
  ☆66Updated 7 years ago
• cgnorthcutt / rankpruning
  🧹 Formerly for binary classification with noisy labels. Replaced by cleanlab.
  ☆82Updated 2 years ago
• enewe101 / word2vec
  An implementation of Mikolov's word2vec in Python using Theano and Lasagne.
  ☆37Updated 7 years ago
• davharris / mcmc-tutorial
  Tutorial introducing Monte Carlo integration and Markov Chain Monte Carlo
  ☆52Updated 12 years ago
• chengsoonong / digbeta
  Active learning for Big Data
  ☆25Updated 6 years ago