Alternatives and similar repositories for kernel-ep:

Users that are interested in kernel-ep are comparing it to the libraries listed below

• HIPS / maxwells-daemon
  Fastidious accounting of entropy streams into and out of optimization and sampling algorithms.
  ☆32Updated 8 years ago
• YingzhenLi / stochastic-EP
  code for stochastic expectation propagation
  ☆16Updated 9 years ago
• davmre / elbow
  Flexible Bayesian inference using TensorFlow
  ☆143Updated 8 years ago
• tlienart / EPBP
  Expectation Particle Belief Propagation code
  ☆12Updated 6 years ago
• blei-lab / deep-exponential-families
  Deep exponential families (DEFs)
  ☆55Updated 7 years ago
• dillonalaird / pysvihmm
  Implementation of stochastic variational inference for Bayesian hidden Markov models.
  ☆66Updated 7 years ago
• SheffieldML / deepGPy
  Deep GPs with GPy
  ☆31Updated 8 years ago
• andymiller / ReducedVarianceReparamGradients
  Reducing Reparameterization Gradient Variance code.
  ☆33Updated 7 years ago
• karlnapf / kernel_hmc
  Code for NIPS 2015 "Gradient-Free Hamiltonian Monte Carlo via Effecient Kernel Exponential Families"
  ☆25Updated 6 years ago
• rueberger / MJHMC
  Python implementation of Markov Jump Hamiltonian Monte Carlo
  ☆24Updated 8 years ago
• SheffieldML / collab
  Collaborative filtering with the GP-LVM
  ☆25Updated 9 years ago
• HIPS / firefly-monte-carlo
  Implementation of an algorithm for Markov chain Monte Carlo with data subsampling
  ☆32Updated 8 years ago
• kzhai / PyNPB
  Non-parametric Bayesian in Python, including Indian buffet process (IBP), hierarchical Dirichlet process (HDP).
  ☆73Updated 9 years ago
• mwhoffman / pybo
  Python package for modular Bayesian optimization
  ☆134Updated 4 years ago
• aschein / pgds
  Poisson-Gamma dynamical systems
  ☆16Updated 8 years ago
• jamesrobertlloyd / automl-phase-1
  2nd place submission to the AutoML competition - phase 1
  ☆22Updated 10 years ago
• jameshensman / VFF
  Variational Fourier Features
  ☆84Updated 3 years ago
• HIPS / Probabilistic-Backpropagation
  Implementation in C and Theano of the method Probabilistic Backpropagation for scalable Bayesian inference in deep neural networks.
  ☆192Updated 6 years ago
• mauriziofilippone / preconditioned_GPs
  Preconditioning Kernel Matrices
  ☆15Updated 8 years ago
• mwhoffman / pygp
  Python package for inference with Gaussian processes
  ☆11Updated 10 years ago
• rgrosse / compositional_structure_search
  ☆46Updated 11 years ago
• SheffieldML / vargplvm
  Bayesian GPLVM in MATLAB and R
  ☆74Updated 7 years ago
• jaanli / proximity_vi
  This code accompanies the proximity variational inference paper.
  ☆18Updated 6 years ago
• mauriziofilippone / deep_gp_random_features
  ☆40Updated 5 years ago
• jamesrobertlloyd / automl-phase-2
  1st place submission to the AutoML competition - phase 2
  ☆28Updated 9 years ago
• gradientinstitute / aboleth
  A bare-bones TensorFlow framework for Bayesian deep learning and Gaussian process approximation
  ☆128Updated 3 years ago
• nitromannitol / stochastic-quasi-newton
  modular implementation of new algorithm
  ☆13Updated 10 years ago
• arahuja / hamiltonian-monte-carlo
  Implementation of Hamiltonian Monte Carlo using Google's TensorFlow
  ☆47Updated 9 years ago
• bshahr / torch-dngo
  Torch implementation of the Deep Network for Global Optimization (DNGO)
  ☆51Updated 8 years ago
• yaoli / GSN
  Efficient implementation of Generative Stochastic Networks
  ☆317Updated 8 years ago