Alternatives and similar repositories for mogptk

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

• pmorenoz / HetMOGP
  Heterogeneous Multi-output Gaussian Processes
  ☆54Updated 5 years ago
• secondmind-labs / GPflux
  Deep GPs built on top of TensorFlow/Keras and GPflow
  ☆127Updated last year
• TyXe-BDL / TyXe
  ☆155Updated 3 years ago
• wesselb / stheno
  Gaussian process modelling in Python
  ☆226Updated last year
• OxfordML / GPz
  GPz 2.0: Heteroscedastic Gaussian processes for uncertain and incomplete data
  ☆49Updated 4 years ago
• SheffieldML / PyDeepGP
  Deep Gaussian Processes in Python
  ☆236Updated 4 years ago
• nchopin / particles
  Sequential Monte Carlo in python
  ☆477Updated 3 months ago
• pmorenoz / ContinualGP
  Continual Gaussian Processes
  ☆31Updated 2 years ago
• PredictiveScienceLab / uq-course
  Introduction to Uncertainty Quantification
  ☆257Updated 3 years ago
• AaltoML / BayesNewton
  Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's method.
  ☆241Updated 2 years ago
• GaussianProcessesCambridge / meetup-resources
  Collection of resources from each meetup event
  ☆13Updated 5 years ago
• sydney-machine-learning / Bayesianneuralnetworks-MCMC-tutorial
  Bayesian neural networks via MCMC: tutorial
  ☆60Updated last year
• cagrell / gp_constr
  Python model for constrained GP
  ☆26Updated 4 years ago
• secondmind-labs / markovflow
  A Tensorflow based library for Time Series Modelling with Gaussian Processes
  ☆32Updated last year
• amzn / orthogonal-additive-gaussian-processes
  Light-weighted code for Orthogonal Additive Gaussian Processes
  ☆43Updated last year
• SURGroup / UQpy
  UQpy (Uncertainty Quantification with python) is a general purpose Python toolbox for modeling uncertainty in physical and mathematical s…
  ☆342Updated last month
• wesselb / gpar
  Implementation of the Gaussian Process Autoregressive Regression Model
  ☆69Updated last year
• secondmind-labs / trieste
  A Bayesian optimization toolbox built on TensorFlow
  ☆244Updated last week
• treforevans / uci_datasets
  Regression datasets from the UCI repository with standardized test-train splits.
  ☆52Updated 3 years ago
• jejjohnson / gp_model_zoo
  Literature and light wrappers for gaussian process models.
  ☆47Updated 4 years ago
• Gabriel-p / pythonMCMC
  A list of Python-based MCMC & ABC packages
  ☆123Updated 7 months ago
• LiuHaiTao01 / SVSHGP
  Stochastic variational heteroscedastic Gaussian process
  ☆15Updated 6 years ago
• jejjohnson / uncertain_gps
  Exploring how to to deal with uncertain inputs with gaussian process regression models.
  ☆27Updated 4 years ago
• fonnesbeck / gp_regression
  A Primer on Gaussian Processes for Regression Analysis (PyData NYC 2019)
  ☆165Updated 4 years ago
• french-paragon / BayesianNeuralNetwork-Tutorial-Metarepos
  A meta repository pointing to the other repositories where the implementation of the supplementary examples for our tutorial "Hands-on Ba…
  ☆139Updated 3 years ago
• helange23 / from_fourier_to_koopman
  Linear and non-linear spectral forecasting algorithms
  ☆139Updated 4 years ago
• alan-turing-institute / mogp-emulator
  Package for fitting Gaussian Process Emulators to multiple output computer simulation results.
  ☆53Updated 2 years ago
• markvdw / RobustGP
  Robust initialisation of inducing points in sparse variational GP regression models.
  ☆34Updated 3 years ago
• thangbui / sparseGP_powerEP
  Unifying sparse approximations for Gaussian process regression and classification, using Power EP
  ☆22Updated 9 years ago
• lee-group-cmu / DeepCDE
  Neural networks for conditional density estimation
  ☆13Updated 5 years ago