Alternatives and similar repositories for Amortized_SVGD:

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

• 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
• enalisnick / paper_summaries
  Summaries and minimal implementations of ML / statistics research articles.
  ☆39Updated 4 years ago
• wittawatj / interpretable-test
  NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.
  ☆63Updated 6 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
• duvenaud / deep-limits
  Repo for a paper about constructing priors on very deep models.
  ☆73Updated 8 years ago
• emtiyaz / vmp-for-svae
  Variational Message Passing for Structured VAE (Code for ICLR 2018 paper)
  ☆44Updated 7 years ago
• t-vi / candlegp
  Gaussian Processes in Pytorch
  ☆75Updated 5 years ago
• slinderman / pypolyagamma
  Fast C code for sampling Polya-gamma random variates. Builds on Jesse Windle's BayesLogit library.
  ☆82Updated 4 years ago
• akshaykgupta / SG_MCMC
  Implementation of Stochastic Gradient MCMC algorithms
  ☆41Updated 8 years ago
• thjashin / spectral-stein-grad
  Code for "A Spectral Approach to Gradient Estimation for Implicit Distributions" (ICML'18)
  ☆33Updated last year
• ssydasheng / FBNN
  Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)
  ☆82Updated 4 years ago
• kasparmartens / NeuralProcesses
  Neural Processes implementation for 1D regression
  ☆65Updated 6 years ago
• cmaddis / astar-sampling
  A generic Monte Carlo method based on the Gumbel-Max trick.
  ☆32Updated 8 years ago
• karlnapf / kernel_exp_family
  Various estimators of the infinite dimensional exponential family model
  ☆15Updated 7 years ago
• andymiller / ReducedVarianceReparamGradients
  Reducing Reparameterization Gradient Variance code.
  ☆33Updated 7 years ago
• markvdw / convgp
  Convolutional Gaussian processes based on GPflow.
  ☆96Updated 7 years ago
• gd-zhang / noisy-K-FAC
  Natural Gradient, Variational Inference
  ☆29Updated 5 years ago
• Bonnevie / rebar
  A Python implementation of the gradient REBAR estimator.
  ☆46Updated 6 years ago
• jameshensman / VFF
  Variational Fourier Features
  ☆84Updated 3 years ago
• UCL-SML / Doubly-Stochastic-DGP
  Deep Gaussian Processes with Doubly Stochastic Variational Inference
  ☆149Updated 6 years ago
• tqchen / ML-SGHMC
  Experiment code for Stochastic Gradient Hamiltonian Monte Carlo
  ☆105Updated 7 years ago
• thjashin / gp-infer-net
  Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019
  ☆41Updated 2 years ago
• wittawatj / kernel-gof
  NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.
  ☆67Updated 5 years ago
• y0ast / VIMCO
  Implementation of "Variational Inference for Monte Carlo Objectives"
  ☆21Updated 4 years ago
• daeilkim / bbvi
  Black Box Variational Inference
  ☆14Updated 9 years ago
• izmailovpavel / TTGP
  ☆26Updated 6 years ago
• davidandrzej / PyIBP
  NumPy implementation of infinite latent feature model (aka Indian Buffet Process or IBP)
  ☆49Updated 7 years ago
• ganguli-lab / deepchaos
  Experiments for the paper "Exponential expressivity in deep neural networks through transient chaos"
  ☆70Updated 8 years ago
• HIPS / author-roulette
  LaTeX package for randomizing author order based on a public seed.
  ☆40Updated 10 years ago