Alternatives and similar repositories for nonstationary-spectral-kernels:

Users that are interested in nonstationary-spectral-kernels are comparing it to the libraries listed below

• sremes / nssm-gp
  Non-stationary spectral mixture kernels implemented in GPflow
  ☆28Updated 6 years ago
• wjmaddox / spectralgp
  Code repo for "Function-Space Distributions over Kernels"
  ☆31Updated 4 years ago
• yorkerlin / VB-MixEF
  Code for ICML 2019 paper on "Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations"
  ☆18Updated 4 years ago
• gianlucadetommaso / Stein-variational-samplers
  Python and MATLAB code for Stein Variational sampling methods
  ☆24Updated 5 years ago
• hegdepashupati / differential-dgp
  Implementation of stochastic variational inference for differentially deep gaussian processes
  ☆15Updated 6 years ago
• FelixOpolka / Deep-Gaussian-Process
  🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0
  ☆27Updated last year
• aboustati / dgplib
  Library for Deep Gaussian Processes based on GPflow
  ☆19Updated 4 years ago
• mauriziofilippone / deep_gp_random_features
  ☆40Updated 5 years ago
• secondmind-labs / markovflow
  A Tensorflow based library for Time Series Modelling with Gaussian Processes
  ☆30Updated 8 months ago
• rmgarnett / gpml_extensions
  Provides various extensions to the GPML toolbox for Gaussian process inference in MATLAB.
  ☆31Updated 7 years ago
• wesselb / gpar
  Implementation of the Gaussian Process Autoregressive Regression Model
  ☆62Updated 2 months ago
• AaltoML / boundary-gp
  Know Your Boundaries: Constraining Gaussian Processes by Variational Harmonic Features
  ☆23Updated 5 years ago
• amzn / orthogonal-additive-gaussian-processes
  Light-weighted code for Orthogonal Additive Gaussian Processes
  ☆41Updated 7 months ago
• blei-lab / variational-smc
  Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)
  ☆65Updated 5 years ago
• jmaronas / TGP.pytorch
  Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021
  ☆24Updated 2 years ago
• AaltoML / hilbert-gp
  Codes for Hilbert space reduced-rank GP regression
  ☆14Updated 5 years ago
• gatsby-sahani / gp-sde
  ☆14Updated last year
• cambridge-mlg / sghmc_dgp
  ☆28Updated 6 years ago
• thangbui / deepGP_approxEP
  see https://github.com/thangbui/geepee for a faster implementation
  ☆37Updated 7 years ago
• Tom-Ryder / VIforSDEs
  A variational method for fast, approximate inference for stochastic differential equations.
  ☆44Updated 6 years ago
• Sohl-Dickstein / Hamiltonian-Annealed-Importance-Sampling
  Matlab code implementing Hamiltonian Annealed Importance Sampling for importance weight, partition function, and log likelihood estimatio…
  ☆26Updated 10 years ago
• thangbui / sparseGP_powerEP
  Unifying sparse approximations for Gaussian process regression and classification, using Power EP
  ☆22Updated 8 years ago
• duvenaud / warped-mixtures
  Code for density estimation with nonparametric cluster shapes.
  ☆38Updated 8 years ago
• RogerFrigola / VGPSSM
  Variational Gaussian Process State-Space Models
  ☆23Updated 9 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
• pierresegonne / VINF
  Repository for DTU Special Course, focusing on Variational Inference using Normalizing Flows (VINF). Supervised by Michael Riis Andersen
  ☆25Updated 4 years ago
• jameshensman / VFF
  Variational Fourier Features
  ☆84Updated 3 years ago
• pmorenoz / ModularGP
  Modular Gaussian Processes
  ☆15Updated 3 years ago
• trappmartin / DeepStructuredMixtures
  Code for Deep Structured Mixtures of Gaussian Processes (DSMGPs)
  ☆11Updated 3 years ago
• vr308 / Generalised-Gaussian-Processes
  Fully Bayesian Inference in GPs - Gaussian and Generic Likelihoods
  ☆22Updated last year