Alternatives and similar repositories for SMS

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

• BigBayes / SGRLD
  Stochastic Gradient Riemannian Langevin Dynamics
  ☆34Updated 10 years ago
• duvenaud / warped-mixtures
  Code for density estimation with nonparametric cluster shapes.
  ☆39Updated 9 years ago
• pawni / BayesByHypernet
  Code for the paper Implicit Weight Uncertainty in Neural Networks
  ☆65Updated 5 years ago
• chrisdxie / in-depth-VI-tutorial
  ☆11Updated 9 years ago
• ssydasheng / Neural-Kernel-Network
  Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326
  ☆71Updated 7 years ago
• tbroderick / streaming_vb
  This is code associated with the paper: Broderick, T, Boyd, N, Wibisono, A, Wilson, AC, and Jordan, MI. Streaming variational Bayes. Neur…
  ☆41Updated 11 years ago
• jameshensman / VFF
  Variational Fourier Features
  ☆85Updated 4 years ago
• shaobohan / VariationalGaussianCopula
  Matlab Code for Variational Gaussian Copula Inference
  ☆16Updated 9 years ago
• TENGBINN / Bayes-by-Backprop
  TensorFlow implementation of Bayes-by-Backprop algorithm from "Weight Uncertainty in Neural Networks" paper
  ☆51Updated 6 years ago
• thangbui / deepGP_approxEP
  see https://github.com/thangbui/geepee for a faster implementation
  ☆37Updated 8 years ago
• achab / nphc
  NPHC
  ☆17Updated 4 years ago
• mauriziofilippone / deep_gp_random_features
  ☆40Updated 6 years ago
• vsmolyakov / DP_means
  Dirichlet Process K-means
  ☆48Updated last year
• namkoong-lab / robustopt
  ☆43Updated 7 years ago
• zixu1986 / Doubly_Stochastic_Gradients
  Code for doubly stochastic gradients
  ☆25Updated 11 years ago
• vveitch / causal-embeddings
  Code for "Using Embeddings to Correct for Unobserved Confounding"
  ☆10Updated 6 years ago
• SheffieldML / deepGP
  Deep Gaussian Processes in matlab
  ☆92Updated 4 years ago
• duvenaud / deep-limits
  Repo for a paper about constructing priors on very deep models.
  ☆73Updated 9 years ago
• csinva / disentangled-attribution-curves
  Using / reproducing DAC from the paper "Disentangled Attribution Curves for Interpreting Random Forests and Boosted Trees"
  ☆28Updated 4 years ago
• cambridge-mlg / sghmc_dgp
  ☆29Updated 6 years ago
• thangbui / geepee
  A collection of Gaussian process models
  ☆30Updated 8 years ago
• wittawatj / kernel-gof
  NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.
  ☆67Updated 6 years ago
• jamesmcinerney / vbmm
  Variational inference for Gaussian mixture models
  ☆35Updated 12 years ago
• blei-lab / zero-inflated-embedding
  Code for the icml paper "zero inflated exponential family embedding"
  ☆29Updated 7 years ago
• akshaykgupta / SG_MCMC
  Implementation of Stochastic Gradient MCMC algorithms
  ☆41Updated 8 years ago
• markvdw / GParML
  Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models.
  ☆43Updated 11 years ago
• arahuja / hamiltonian-monte-carlo
  Implementation of Hamiltonian Monte Carlo using Google's TensorFlow
  ☆46Updated 9 years ago
• andymiller / ReducedVarianceReparamGradients
  Reducing Reparameterization Gradient Variance code.
  ☆33Updated 8 years ago
• dillonalaird / pysvihmm
  Implementation of stochastic variational inference for Bayesian hidden Markov models.
  ☆68Updated 8 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 5 years ago