Alternatives and similar repositories for warped-mixtures:

Users that are interested in warped-mixtures are comparing it to the libraries listed below

• andymiller / ReducedVarianceReparamGradients
  Reducing Reparameterization Gradient Variance code.
  ☆33Updated 7 years ago
• jameshensman / VFF
  Variational Fourier Features
  ☆83Updated 3 years ago
• emtiyaz / vmp-for-svae
  Variational Message Passing for Structured VAE (Code for ICLR 2018 paper)
  ☆44Updated 6 years ago
• wittawatj / kernel-gof
  NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.
  ☆67Updated 5 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
• mauriziofilippone / deep_gp_random_features
  ☆40Updated 5 years ago
• kasparmartens / NeuralProcesses
  Neural Processes implementation for 1D regression
  ☆65Updated 6 years ago
• IraKorshunova / bruno
  a deep recurrent model for exchangeable data
  ☆34Updated 4 years ago
• wittawatj / interpretable-test
  NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.
  ☆63Updated 6 years ago
• karlnapf / kernel_hmc
  Code for NIPS 2015 "Gradient-Free Hamiltonian Monte Carlo via Effecient Kernel Exponential Families"
  ☆25Updated 6 years ago
• BigBayes / SGRLD
  Stochastic Gradient Riemannian Langevin Dynamics
  ☆33Updated 9 years ago
• thangbui / geepee
  A collection of Gaussian process models
  ☆30Updated 7 years ago
• AMLab-Amsterdam / SEVDL_MGP
  Example implementation of the Bayesian neural network in "Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteri…
  ☆30Updated 4 years ago
• markvdw / convgp
  Convolutional Gaussian processes based on GPflow.
  ☆96Updated 7 years ago
• adjidieng / REM
  Reweighted Expectation Maximization
  ☆29Updated 5 years ago
• franrruiz / vcd_divergence
  Code to minimize the Variational Contrastive Divergence (VCD)
  ☆29Updated 5 years ago
• duvenaud / deep-limits
  Repo for a paper about constructing priors on very deep models.
  ☆72Updated 8 years ago
• wjmaddox / spectralgp
  Code repo for "Function-Space Distributions over Kernels"
  ☆31Updated 4 years ago
• sremes / nssm-gp
  Non-stationary spectral mixture kernels implemented in GPflow
  ☆28Updated 6 years ago
• markvdw / GParML
  Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models.
  ☆43Updated 11 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
• t-vi / candlegp
  Gaussian Processes in Pytorch
  ☆75Updated 5 years ago
• wittawatj / kernel-mod
  NeurIPS 2018. Linear-time model comparison tests.
  ☆18Updated 5 years ago
• blei-lab / ars-reparameterization
  Source code for Naesseth et. al. "Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms" (2017)
  ☆39Updated 7 years ago
• didriknielsen / ds3_abi_exercises
  Exercises for the Tutorial on Approximate Bayesian Inference at the Data Science Summer School 2018
  ☆22Updated 6 years ago
• akshaykgupta / SG_MCMC
  Implementation of Stochastic Gradient MCMC algorithms
  ☆40Updated 8 years ago
• hegdepashupati / differential-dgp
  Implementation of stochastic variational inference for differentially deep gaussian processes
  ☆15Updated 6 years ago
• Sohl-Dickstein / Minimum-Probability-Flow-Learning
  Matlab code implementing Minimum Probability Flow Learning.
  ☆68Updated 10 years ago
• tbrx / compiled-inference
  Train neural networks to use as SMC and importance sampling proposals
  ☆24Updated 7 years ago
• duvenaud / learn-discrete
  Graduate topics course on learning discrete latent structure.
  ☆67Updated 6 years ago