Alternatives and similar repositories for thesis:

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

• andymiller / ReducedVarianceReparamGradients
  Reducing Reparameterization Gradient Variance code.
  ☆33Updated 7 years ago
• BigBayes / SGRLD
  Stochastic Gradient Riemannian Langevin Dynamics
  ☆33Updated 9 years ago
• Sohl-Dickstein / Minimum-Probability-Flow-Learning
  Matlab code implementing Minimum Probability Flow Learning.
  ☆68Updated 10 years ago
• HIPS / maxwells-daemon
  Fastidious accounting of entropy streams into and out of optimization and sampling algorithms.
  ☆32Updated 8 years ago
• HIPS / firefly-monte-carlo
  Implementation of an algorithm for Markov chain Monte Carlo with data subsampling
  ☆32Updated 8 years ago
• wittawatj / kernel-mod
  NeurIPS 2018. Linear-time model comparison tests.
  ☆18Updated 5 years ago
• wittawatj / interpretable-test
  NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.
  ☆63Updated 6 years ago
• Sohl-Dickstein / LAHMC
  Look Ahead Hamiltonian Monte Carlo
  ☆30Updated 10 years ago
• wittawatj / kernel-gof
  NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.
  ☆67Updated 5 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
• karlnapf / ds3_kernel_testing
  Material for the practical of the DS3 course on "Representing and comparing probabilities with kernels"
  ☆26Updated 6 years ago
• duvenaud / warped-mixtures
  Code for density estimation with nonparametric cluster shapes.
  ☆38Updated 8 years ago
• IraKorshunova / bruno
  a deep recurrent model for exchangeable data
  ☆34Updated 4 years ago
• duvenaud / deep-limits
  Repo for a paper about constructing priors on very deep models.
  ☆73Updated 8 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
• ebonilla / AutoGP
  Code for AutoGP
  ☆26Updated 5 years ago
• mrkulk / SequentialInference
  Dirichlet Process Mixture using PVI, SMC, Variational
  ☆15Updated 10 years ago
• jameshensman / VFF
  Variational Fourier Features
  ☆84Updated 3 years ago
• pawni / BayesByHypernet
  Code for the paper Implicit Weight Uncertainty in Neural Networks
  ☆65Updated 5 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
• thangbui / deepGP_approxEP
  see https://github.com/thangbui/geepee for a faster implementation
  ☆37Updated 7 years ago
• rgiordan / CovariancesRobustnessVBPaper
  ☆11Updated last year
• akshaykgupta / SG_MCMC
  Implementation of Stochastic Gradient MCMC algorithms
  ☆41Updated 8 years ago
• karlnapf / kernel_hmc
  Code for NIPS 2015 "Gradient-Free Hamiltonian Monte Carlo via Effecient Kernel Exponential Families"
  ☆25Updated 6 years ago
• lxuechen / BDMC
  PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.
  ☆52Updated 3 years ago
• rueberger / MJHMC
  Python implementation of Markov Jump Hamiltonian Monte Carlo
  ☆24Updated 8 years ago
• markvdw / convgp
  Convolutional Gaussian processes based on GPflow.
  ☆96Updated 7 years ago
• mijungi / lllvm
  ☆16Updated 9 years ago
• mauriziofilippone / deep_gp_random_features
  ☆40Updated 5 years ago
• HIPS / hips-lib
  Library of common tools for machine learning research.
  ☆41Updated 7 years ago