Alternatives and similar repositories for GP-CaKe-project:

Users that are interested in GP-CaKe-project are comparing it to the libraries listed below

• rueberger / MJHMC
  Python implementation of Markov Jump Hamiltonian Monte Carlo
  ☆24Updated 8 years ago
• edwardlib / papers
  Edward content including papers, posters, and talks
  ☆90Updated 4 years ago
• andymiller / ReducedVarianceReparamGradients
  Reducing Reparameterization Gradient Variance code.
  ☆33Updated 7 years ago
• ofirnachum / uncertainty_gbm
  Sklearn implementation of GBM to predict mu(X) and std(X) on heteroscedastic data
  ☆26Updated 8 years ago
• gregversteeg / discrete_sieve
  The information sieve for discrete variables.
  ☆36Updated 8 years ago
• blei-lab / deep-exponential-families
  Deep exponential families (DEFs)
  ☆55Updated 7 years ago
• SheffieldML / collab
  Collaborative filtering with the GP-LVM
  ☆25Updated 9 years ago
• HIPS / hips-lib
  Library of common tools for machine learning research.
  ☆41Updated 7 years ago
• ferrine / gelato
  Bayesian dessert for Lasagne
  ☆84Updated 7 years ago
• casmls / casmls.github.io
  Columbia Advanced Machine Learning Seminar
  ☆24Updated 6 years ago
• dillonalaird / pysvihmm
  Implementation of stochastic variational inference for Bayesian hidden Markov models.
  ☆66Updated 7 years ago
• jameshensman / VFF
  Variational Fourier Features
  ☆84Updated 3 years ago
• HIPS / maxwells-daemon
  Fastidious accounting of entropy streams into and out of optimization and sampling algorithms.
  ☆32Updated 8 years ago
• vene / pyowl
  Ordered Weighted L1 regularization for classification and regression in Python
  ☆52Updated 6 years ago
• aatapa / RLScore
  ☆67Updated last year
• PMBio / pygp
  A Gaussian process toolbox in python
  ☆42Updated 12 years ago
• wittawatj / interpretable-test
  NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.
  ☆63Updated 6 years ago
• duvenaud / deep-limits
  Repo for a paper about constructing priors on very deep models.
  ☆72Updated 8 years ago
• powerscorinne / GLRM
  ☆98Updated 7 years ago
• junpenglao / Bayesian-Cognitive-Modeling-in-Pymc3
  PyMC3 codes of Lee and Wagenmakers' Bayesian Cognitive Modeling - A Pratical Course
  ☆96Updated 7 years ago
• franrruiz / p-emb
  Exponential family embeddings (Poisson or Bernoulli) for discrete data
  ☆32Updated 5 years ago
• mrkulk / SequentialInference
  Dirichlet Process Mixture using PVI, SMC, Variational
  ☆15Updated 10 years ago
• akshaykgupta / SG_MCMC
  Implementation of Stochastic Gradient MCMC algorithms
  ☆40Updated 8 years ago
• drckf / paysage
  Unsupervised learning and generative models in python/pytorch.
  ☆119Updated 2 years ago
• hrayrhar / T-CorEx
  Implementation of linear CorEx and temporal CorEx.
  ☆37Updated 3 years ago
• lucastheis / cmt
  Fast CPU implementations of several conditional probabilistic models
  ☆36Updated last year
• jaanli / proximity_vi
  This code accompanies the proximity variational inference paper.
  ☆18Updated 6 years ago
• Jianbo-Lab / CCM
  ☆74Updated 6 years ago
• blei-lab / zero-inflated-embedding
  Code for the icml paper "zero inflated exponential family embedding"
  ☆29Updated 7 years ago
• ryotat / mlss15
  ☆58Updated 9 years ago