Alternatives and similar repositories for sgmcmc

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

• akshaykgupta / SG_MCMC
  Implementation of Stochastic Gradient MCMC algorithms
  ☆41Updated 8 years ago
• duvenaud / deep-limits
  Repo for a paper about constructing priors on very deep models.
  ☆73Updated 9 years ago
• slinderman / pypolyagamma
  Fast C code for sampling Polya-gamma random variates. Builds on Jesse Windle's BayesLogit library.
  ☆83Updated 5 years ago
• imurray / chol-rev
  Backpropagate derivatives through the Cholesky decomposition
  ☆58Updated 5 years ago
• andymiller / ReducedVarianceReparamGradients
  Reducing Reparameterization Gradient Variance code.
  ☆33Updated 8 years ago
• HIPS / maxwells-daemon
  Fastidious accounting of entropy streams into and out of optimization and sampling algorithms.
  ☆33Updated 9 years ago
• HIPS / Probabilistic-Backpropagation
  Implementation in C and Theano of the method Probabilistic Backpropagation for scalable Bayesian inference in deep neural networks.
  ☆191Updated 6 years ago
• jameshensman / VFF
  Variational Fourier Features
  ☆85Updated 4 years ago
• SheffieldML / deepGPy
  Deep GPs with GPy
  ☆31Updated 9 years ago
• RuiShu / nn-bayesian-optimization
  We use a modified neural network instead of Gaussian process for Bayesian optimization.
  ☆108Updated 8 years ago
• gradientinstitute / aboleth
  A bare-bones TensorFlow framework for Bayesian deep learning and Gaussian process approximation
  ☆128Updated 4 years ago
• tqchen / ML-SGHMC
  Experiment code for Stochastic Gradient Hamiltonian Monte Carlo
  ☆106Updated 7 years ago
• ferrine / gelato
  Bayesian dessert for Lasagne
  ☆83Updated 8 years ago
• HIPS / firefly-monte-carlo
  Implementation of an algorithm for Markov chain Monte Carlo with data subsampling
  ☆32Updated 9 years ago
• BigBayes / SGRLD
  Stochastic Gradient Riemannian Langevin Dynamics
  ☆34Updated 10 years ago
• HIPS / pgmult
  Dependent multinomials made easy: stick-breaking with the Pólya-gamma augmentation
  ☆61Updated 4 years ago
• stepelu / ptstat
  Probabilistic Programming and Statistical Inference in PyTorch
  ☆110Updated 8 years ago
• wittawatj / kernel-gof
  NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.
  ☆67Updated 6 years ago
• t-vi / candlegp
  Gaussian Processes in Pytorch
  ☆75Updated 5 years ago
• brain-research / l2hmc
  TensorFlow implementation for training MCMC samplers from the paper: Generalizing Hamiltonian Monte Carlo with Neural Network
  ☆183Updated 7 years ago
• enalisnick / paper_summaries
  Summaries and minimal implementations of ML / statistics research articles.
  ☆39Updated 4 years ago
• rgiordan / CovariancesRobustnessVBPaper
  ☆12Updated 2 years ago
• kasparmartens / NeuralProcesses
  Neural Processes implementation for 1D regression
  ☆64Updated 6 years ago
• yaringal / DropoutUncertaintyDemos
  What My Deep Model Doesn't Know...
  ☆116Updated 9 years ago
• markvdw / convgp
  Convolutional Gaussian processes based on GPflow.
  ☆95Updated 7 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
• 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
• rueberger / MJHMC
  Python implementation of Markov Jump Hamiltonian Monte Carlo
  ☆24Updated 8 years ago
• google-research / autoconj
  Recognizing and exploiting conjugacy without a domain-specific language
  ☆36Updated 5 years ago
• mauriziofilippone / deep_gp_random_features
  ☆40Updated 6 years ago