Alternatives and similar repositories for agp:

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

• trungngv / gprn
  Code for the paper 'Efficient Variational Inference for Gaussian Process Regression Networks'
  ☆22Updated 11 years ago
• andymiller / ReducedVarianceReparamGradients
  Reducing Reparameterization Gradient Variance code.
  ☆33Updated 7 years ago
• BigBayes / SGRLD
  Stochastic Gradient Riemannian Langevin Dynamics
  ☆33Updated 9 years ago
• mrkulk / SequentialInference
  Dirichlet Process Mixture using PVI, SMC, Variational
  ☆15Updated 10 years ago
• HIPS / firefly-monte-carlo
  Implementation of an algorithm for Markov chain Monte Carlo with data subsampling
  ☆32Updated 8 years ago
• HIPS / maxwells-daemon
  Fastidious accounting of entropy streams into and out of optimization and sampling algorithms.
  ☆32Updated 8 years ago
• ebonilla / AutoGP
  Code for AutoGP
  ☆26Updated 5 years ago
• karlnapf / kernel_hmc
  Code for NIPS 2015 "Gradient-Free Hamiltonian Monte Carlo via Effecient Kernel Exponential Families"
  ☆25Updated 6 years ago
• rgiordan / CovariancesRobustnessVBPaper
  ☆11Updated last year
• dillonalaird / pysvihmm
  Implementation of stochastic variational inference for Bayesian hidden Markov models.
  ☆65Updated 7 years ago
• Sohl-Dickstein / LAHMC
  Look Ahead Hamiltonian Monte Carlo
  ☆30Updated 9 years ago
• duvenaud / deep-limits
  Repo for a paper about constructing priors on very deep models.
  ☆72Updated 8 years ago
• rgiordan / LinearResponseVariationalBayesNIPS2015
  Code and text for our NIPS 2015 paper on linear response variational Bayes
  ☆19Updated 7 years ago
• SheffieldML / collab
  Collaborative filtering with the GP-LVM
  ☆25Updated 9 years ago
• Sohl-Dickstein / Minimum-Probability-Flow-Learning
  Matlab code implementing Minimum Probability Flow Learning.
  ☆68Updated 10 years ago
• shraman-rc / vae
  Fun with variational autoencoders.
  ☆11Updated 7 years ago
• SheffieldML / ChainedGP
  Repository for Chained Gaussian Processes
  ☆14Updated 8 years ago
• cangermueller / vbmfa
  Variational Bayesian Mixture of Factor Analysers
  ☆22Updated 10 years ago
• YingzhenLi / stochastic-EP
  code for stochastic expectation propagation
  ☆16Updated 9 years ago
• GRAAL-Research / PAC-Bayes_sample_compress_for_kernel_methods
  Learning algorithms introduced in "A PAC-Bayes Sample Compression Approach to Kernel Methods" (ICML 2011)
  ☆9Updated 10 years ago
• tansey / vsmrfs
  Vector-Space Markov Random Fields
  ☆21Updated 9 years ago
• rgrosse / compositional_structure_search
  ☆46Updated 11 years ago
• holdenlee / simons-ml
  Notes from Simons Institute program "Foundations of Machine Learning"
  ☆13Updated 7 years ago
• franrruiz / vcd_divergence
  Code to minimize the Variational Contrastive Divergence (VCD)
  ☆28Updated 5 years ago
• jameshensman / VFF
  Variational Fourier Features
  ☆83Updated 3 years ago
• rueberger / MJHMC
  Python implementation of Markov Jump Hamiltonian Monte Carlo
  ☆24Updated 7 years ago
• markvdw / GParML
  Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models.
  ☆43Updated 10 years ago
• thangbui / geepee
  A collection of Gaussian process models
  ☆30Updated 7 years ago
• mwhoffman / pygp
  Python package for inference with Gaussian processes
  ☆11Updated 9 years ago
• enalisnick / paper_summaries
  Summaries and minimal implementations of ML / statistics research articles.
  ☆39Updated 3 years ago