Alternatives and similar repositories for gprf

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

• imurray / chol-rev
  Backpropagate derivatives through the Cholesky decomposition
  ☆58Updated 5 years ago
• SheffieldML / deepGPy
  Deep GPs with GPy
  ☆31Updated 9 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
• duvenaud / deep-limits
  Repo for a paper about constructing priors on very deep models.
  ☆73Updated 9 years ago
• tqchen / ML-SGHMC
  Experiment code for Stochastic Gradient Hamiltonian Monte Carlo
  ☆106Updated 7 years ago
• jameshensman / VFF
  Variational Fourier Features
  ☆85Updated 4 years ago
• bshahr / torch-dngo
  Torch implementation of the Deep Network for Global Optimization (DNGO)
  ☆51Updated 9 years ago
• gpapamak / epsilon_free_inference
  Code for paper "Fast ε-free Inference of Simulation Models with Bayesian Conditional Density Estimation"
  ☆32Updated 6 years ago
• t-vi / candlegp
  Gaussian Processes in Pytorch
  ☆75Updated 5 years ago
• markvdw / convgp
  Convolutional Gaussian processes based on GPflow.
  ☆95Updated 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
• dillonalaird / pysvihmm
  Implementation of stochastic variational inference for Bayesian hidden Markov models.
  ☆69Updated 7 years ago
• arahuja / hamiltonian-monte-carlo
  Implementation of Hamiltonian Monte Carlo using Google's TensorFlow
  ☆46Updated 9 years ago
• markvdw / GParML
  Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models.
  ☆43Updated 11 years ago
• PMBio / pygp
  A Gaussian process toolbox in python
  ☆42Updated 13 years ago
• casmls / casmls.github.io
  Columbia Advanced Machine Learning Seminar
  ☆24Updated 7 years ago
• ebonilla / AutoGP
  Code for AutoGP
  ☆27Updated 6 years ago
• Nat-D / SVAE-Torch
  ☆11Updated 8 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
• BigBayes / SGRLD
  Stochastic Gradient Riemannian Langevin Dynamics
  ☆34Updated 10 years ago
• yaoli / nade_k
  An iterative neural autoregressive distribution estimator (NADE-K)
  ☆26Updated 10 years ago
• SheffieldML / ChainedGP
  Repository for Chained Gaussian Processes
  ☆14Updated 9 years ago
• Bihaqo / exp-machines
  Exponential Machines implementation
  ☆42Updated 6 months ago
• RuiShu / kaos
  Deep variational inference library for Keras
  ☆15Updated 8 years ago
• wittawatj / interpretable-test
  NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.
  ☆64Updated 7 years ago
• karlnapf / kernel_hmc
  Code for NIPS 2015 "Gradient-Free Hamiltonian Monte Carlo via Effecient Kernel Exponential Families"
  ☆25Updated 7 years ago
• ml-lab / auxiliary-deep-generative-models
  Implementation of auxiliary deep generative models for semi-supervised learning
  ☆28Updated 9 years ago
• muupan / deep-ensemble-uncertainty
  An implementation of "Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles" (http://arxiv.org/abs/1612.01474)
  ☆35Updated 8 years ago
• karlnapf / kameleon-mcmc
  Code for Kernel Adaptive Metropolis-Hastings
  ☆33Updated 10 years ago