Alternatives and similar repositories for uncertain_gps

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

• plugyawn / gp-zoo
  A repository with implementations of major papers on Gaussian Process regression models, implemented from scratch in Python, notably incl…
  ☆14Updated 3 years ago
• j-wilson / GPflowSampling
  Code for efficiently sampling functions from GP(flow) posteriors
  ☆74Updated 5 years ago
• LiuHaiTao01 / SVSHGP
  Stochastic variational heteroscedastic Gaussian process
  ☆15Updated 6 years ago
• secondmind-labs / markovflow
  A Tensorflow based library for Time Series Modelling with Gaussian Processes
  ☆32Updated last year
• wjmaddox / online_gp
  Code repo for "Kernel Interpolation for Scalable Online Gaussian Processes"
  ☆64Updated 4 years ago
• shalijiang / bo
  code for BINOCULARS and Multi-Step BO
  ☆12Updated 5 years ago
• aidanscannell / GPJax
  Minimal Gaussian process library in JAX with a simple (custom) approach to state management.
  ☆12Updated 2 years ago
• AaltoML / spatio-temporal-GPs
  Code for NeurIPS 2021 paper 'Spatio-Temporal Variational Gaussian Processes'
  ☆47Updated 4 years ago
• wesselb / neuralprocesses
  A framework for composing Neural Processes in Python
  ☆89Updated last year
• PredictiveIntelligenceLab / GP-NODEs
  ☆28Updated 3 years ago
• cagatayyildiz / npde
  Nonparametric Differential Equation Modeling
  ☆56Updated last year
• jmaronas / TGP.pytorch
  Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021
  ☆25Updated 3 years ago
• amzn / orthogonal-additive-gaussian-processes
  Light-weighted code for Orthogonal Additive Gaussian Processes
  ☆43Updated last year
• yucenli / bnn-bo
  Bayesian Neural Network Surrogates for Bayesian Optimization
  ☆65Updated last year
• pnnl / NeuralDAEs
  Learning Neural Differential Algebraic Equations via Operator Splitting
  ☆21Updated 5 months ago
• thangbui / sparseGP_powerEP
  Unifying sparse approximations for Gaussian process regression and classification, using Power EP
  ☆22Updated 9 years ago
• secondmind-labs / GPflux
  Deep GPs built on top of TensorFlow/Keras and GPflow
  ☆127Updated last year
• jejjohnson / gp_model_zoo
  Literature and light wrappers for gaussian process models.
  ☆47Updated 4 years ago
• fidero / gp-derivative
  Example code to speed up GP inference with gradients for high-dimensional inputs.
  ☆14Updated 4 years ago
• Machine-Learning-Dynamical-Systems / kooplearn
  A Python package to learn the Koopman operator.
  ☆65Updated last week
• cagrell / gp_constr
  Python model for constrained GP
  ☆26Updated 4 years ago
• sremes / nssm-gp
  Non-stationary spectral mixture kernels implemented in GPflow
  ☆28Updated 7 years ago
• pmorenoz / HetMOGP
  Heterogeneous Multi-output Gaussian Processes
  ☆54Updated 5 years ago
• GAMES-UChile / mogptk
  Multi-Output Gaussian Process Toolkit
  ☆182Updated 6 months ago
• pmorenoz / ModularGP
  Modular Gaussian Processes
  ☆16Updated 4 years ago
• ltiao / bore
  Bayesian Optimization with Density-Ratio Estimation
  ☆24Updated 3 years ago
• spbu-math-cs / Riemannian-Gaussian-Processes
  Supplementary code for the NeurIPS 2020 paper "Matern Gaussian processes on Riemannian manifolds".
  ☆29Updated 10 months ago
• cambridge-mlg / sgd-gp
  Public code for running Stochastic Gradient Descent on GPs.
  ☆39Updated 8 months ago
• trappmartin / DeepStructuredMixtures
  Code for Deep Structured Mixtures of Gaussian Processes (DSMGPs)
  ☆11Updated 3 years ago
• thangbui / streaming_sparse_gp
  Streaming sparse Gaussian process approximations
  ☆69Updated 3 years ago