Alternatives and similar repositories for Doubly-Stochastic-DGP

Users that are interested in Doubly-Stochastic-DGP are comparing it to the libraries listed below

• SheffieldML / PyDeepGP
  Deep Gaussian Processes in Python
  ☆234Updated 4 years ago
• markvdw / convgp
  Convolutional Gaussian processes based on GPflow.
  ☆95Updated 7 years ago
• hughsalimbeni / bayesian_benchmarks
  A community repository for benchmarking Bayesian methods
  ☆110Updated 3 years ago
• kasparmartens / NeuralProcesses
  Neural Processes implementation for 1D regression
  ☆65Updated 6 years ago
• aboustati / dgplib
  Library for Deep Gaussian Processes based on GPflow
  ☆19Updated 5 years ago
• cambridge-mlg / sghmc_dgp
  ☆28Updated 6 years ago
• secondmind-labs / GPflux
  Deep GPs built on top of TensorFlow/Keras and GPflow
  ☆125Updated 8 months ago
• tqchen / ML-SGHMC
  Experiment code for Stochastic Gradient Hamiltonian Monte Carlo
  ☆105Updated 7 years ago
• ssydasheng / FBNN
  Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)
  ☆85Updated 4 years ago
• brain-research / nngp
  Deep neural network kernel for Gaussian process
  ☆207Updated 4 years ago
• maka89 / Deep-Kernel-GP
  Deep Kernel Learning. Gaussian Process Regression where the input is a neural network mapping of x that maximizes the marginal likelihood
  ☆93Updated 7 years ago
• FelixOpolka / Deep-Gaussian-Process
  🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0
  ☆26Updated last year
• SheffieldML / deepGP
  Deep Gaussian Processes in matlab
  ☆93Updated 3 years ago
• wjmaddox / spectralgp
  Code repo for "Function-Space Distributions over Kernels"
  ☆31Updated 4 years ago
• t-vi / candlegp
  Gaussian Processes in Pytorch
  ☆75Updated 5 years ago
• hughsalimbeni / DGPs_with_IWVI
  Deep Gaussian Processes with Importance-Weighted Variational Inference
  ☆39Updated 6 years ago
• automl / pybnn
  Bayesian neural network package
  ☆147Updated 3 years ago
• pmorenoz / HetMOGP
  Heterogeneous Multi-output Gaussian Processes
  ☆52Updated 5 years ago
• sremes / nssm-gp
  Non-stationary spectral mixture kernels implemented in GPflow
  ☆28Updated 6 years ago
• kekeblom / DeepCGP
  Deep convolutional gaussian processes.
  ☆78Updated 5 years ago
• kirthevasank / add-gp-bandits
  Additive Gaussian Process Bandits - version 1.0
  ☆27Updated 8 years ago
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆48Updated 5 years ago
• microsoft / deterministic-variational-inference
  Sample code for running deterministic variational inference to train Bayesian neural networks
  ☆100Updated 6 years ago
• thangbui / deepGP_approxEP
  see https://github.com/thangbui/geepee for a faster implementation
  ☆37Updated 8 years ago
• j-wilson / GPflowSampling
  Code for efficiently sampling functions from GP(flow) posteriors
  ☆72Updated 4 years ago
• blei-lab / variational-smc
  Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)
  ☆65Updated 6 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
• rmgarnett / gpml_extensions
  Provides various extensions to the GPML toolbox for Gaussian process inference in MATLAB.
  ☆32Updated 8 years ago
• jameshensman / VFF
  Variational Fourier Features
  ☆86Updated 4 years ago
• wjmaddox / drbayes
  Code Repo for "Subspace Inference for Bayesian Deep Learning"
  ☆82Updated last year