Alternatives and similar repositories for NIPS2015:

Users that are interested in NIPS2015 are comparing it to the libraries listed below

• BigBayes / BNPMix.jl
  Bayesian Nonparametric Mixture Models in Julia
  ☆14Updated 7 years ago
• yaringal / VSSGP
  Variational Sparse Spectrum Gaussian Process toolkit
  ☆22Updated 9 years ago
• sremes / nssm-gp
  Non-stationary spectral mixture kernels implemented in GPflow
  ☆28Updated 6 years ago
• tlienart / EPBP
  Expectation Particle Belief Propagation code
  ☆12Updated 6 years ago
• ssydasheng / Neural-Kernel-Network
  Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326
  ☆71Updated 6 years ago
• jgorham / SteinDiscrepancy.jl
  Practical tools for quantifying how well a sample approximates a target distribution
  ☆27Updated 4 years ago
• blei-lab / variational-smc
  Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)
  ☆65Updated 5 years ago
• andymiller / vboost
  code supplement for variational boosting (https://arxiv.org/abs/1611.06585)
  ☆11Updated 7 years ago
• karlnapf / kernel_hmc
  Code for NIPS 2015 "Gradient-Free Hamiltonian Monte Carlo via Effecient Kernel Exponential Families"
  ☆25Updated 6 years ago
• Sohl-Dickstein / Minimum-Probability-Flow-Learning
  Matlab code implementing Minimum Probability Flow Learning.
  ☆68Updated 10 years ago
• BigBayes / SGMCMC.jl
  Stochastic Gradient Markov Chain Monte Carlo and Optimisation
  ☆17Updated 8 years ago
• tbrx / compiled-inference
  Train neural networks to use as SMC and importance sampling proposals
  ☆24Updated 7 years ago
• Sohl-Dickstein / LAHMC
  Look Ahead Hamiltonian Monte Carlo
  ☆30Updated 10 years ago
• mauriziofilippone / preconditioned_GPs
  Preconditioning Kernel Matrices
  ☆15Updated 8 years ago
• jgorham / stein_discrepancy
  Code to compute the Stein discrepancy between a sample distribution and its target
  ☆16Updated 7 years ago
• AaltoML / boundary-gp
  Know Your Boundaries: Constraining Gaussian Processes by Variational Harmonic Features
  ☆23Updated 5 years ago
• aki-nishimura / discontinuous-hmc
  "Discontinuous Hamiltonian Monte Carlo for sampling discrete parameters" by Akihiko Nishimura, David Dunson, Jianfeng Lu
  ☆27Updated 6 years ago
• gianlucadetommaso / Stein-variational-samplers
  Python and MATLAB code for Stein Variational sampling methods
  ☆25Updated 5 years ago
• stokasto / sgmcmc
  Stochastic Gradient MCMC algorithms implemented in theano (and autograd)
  ☆10Updated 8 years ago
• andymiller / ReducedVarianceReparamGradients
  Reducing Reparameterization Gradient Variance code.
  ☆33Updated 7 years ago
• rgiordan / paragami
  "Parameter origami" -- folding and unfolding collections of parameters for optimization and sensitivity analysis.
  ☆14Updated last year
• hegdepashupati / differential-dgp
  Implementation of stochastic variational inference for differentially deep gaussian processes
  ☆15Updated 6 years ago
• duvenaud / harlemcmc-shake
  Code to produce demos of Metroplis-Hastings and Hamiltonian Monte Carlo samplers.
  ☆37Updated 11 years ago
• yorkerlin / VB-MixEF
  Code for ICML 2019 paper on "Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations"
  ☆18Updated 4 years ago
• pyro-ppl / pyro-api
  Generic API for dispatch to Pyro backends.
  ☆16Updated 3 years ago
• fhuszar / thesis
  my PhD thesis on Bayesian inference
  ☆27Updated 11 years ago
• philipphennig / probabilistic-numerics.org
  This repository houses the code for the community website http://www.probabilistic-numerics.org
  ☆35Updated 4 years ago
• hughsalimbeni / DGPs_with_IWVI
  Deep Gaussian Processes with Importance-Weighted Variational Inference
  ☆38Updated 5 years ago
• akshaykgupta / SG_MCMC
  Implementation of Stochastic Gradient MCMC algorithms
  ☆41Updated 8 years ago
• duvenaud / jaxde
  Prototypes of differentiable differential equation solvers in JAX.
  ☆27Updated 5 years ago