Alternatives and similar repositories for gp_constr

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

• jejjohnson / uncertain_gps
  Exploring how to to deal with uncertain inputs with gaussian process regression models.
  ☆27Updated 4 years ago
• PredictiveIntelligenceLab / GP-NODEs
  ☆29Updated 2 years ago
• secondmind-labs / GPflux
  Deep GPs built on top of TensorFlow/Keras and GPflow
  ☆127Updated 9 months ago
• Machine-Learning-Dynamical-Systems / kooplearn
  A Python package to learn the Koopman operator.
  ☆60Updated 8 months ago
• j-wilson / GPflowSampling
  Code for efficiently sampling functions from GP(flow) posteriors
  ☆72Updated 4 years ago
• GAMES-UChile / mogptk
  Multi-Output Gaussian Process Toolkit
  ☆175Updated 2 months ago
• BethanyL / DeepKoopman
  neural networks to learn Koopman eigenfunctions
  ☆421Updated last year
• sklus / d3s
  Data-driven dynamical systems toolbox.
  ☆74Updated last week
• dynamicslab / pykoopman
  A package for computing data-driven approximations to the Koopman operator.
  ☆373Updated 9 months ago
• NoemieJaquier / MaternGaBO
  This repository contains the code for the paper "Geometry-aware Bayesian Optimization in Roboticsusing Riemannian Matérn Kernels" (CoRL'2…
  ☆20Updated 2 years ago
• thangbui / streaming_sparse_gp
  Streaming sparse Gaussian process approximations
  ☆67Updated 2 years ago
• LiuHaiTao01 / SVSHGP
  Stochastic variational heteroscedastic Gaussian process
  ☆15Updated 6 years ago
• GaloisInc / dlkoopman
  A general-purpose Python package for Koopman theory using deep learning.
  ☆106Updated 6 months ago
• hvarfner / vanilla_bo_in_highdim
  ☆29Updated 5 months ago
• cagatayyildiz / npde
  Nonparametric Differential Equation Modeling
  ☆54Updated last year
• martinjankowiak / saasbo
  SAASBO: a package for high-dimensional bayesian optimization
  ☆44Updated 3 years ago
• fusion-ml / OCBO
  Offline Contextual Bayesian Optimization
  ☆14Updated 2 years ago
• yucenli / bnn-bo
  Bayesian Neural Network Surrogates for Bayesian Optimization
  ☆53Updated last year
• pmorenoz / HetMOGP
  Heterogeneous Multi-output Gaussian Processes
  ☆52Updated 5 years ago
• OxfordML / GPz
  GPz 2.0: Heteroscedastic Gaussian processes for uncertain and incomplete data
  ☆49Updated 4 years ago
• Crunch-UQ4MI / neuraluq
  ☆184Updated 4 months ago
• secondmind-labs / trieste
  A Bayesian optimization toolbox built on TensorFlow
  ☆238Updated last month
• marvinpfoertner / linpde-gp
  Code for the Paper "Physics-Informed Gaussian Process Regression Generalizes Linear PDE Solvers"
  ☆30Updated last year
• amzn / orthogonal-additive-gaussian-processes
  Light-weighted code for Orthogonal Additive Gaussian Processes
  ☆43Updated last year
• decargroup / pykoop
  Koopman operator identification library in Python, compatible with `scikit-learn`
  ☆80Updated 3 weeks ago
• wjmaddox / online_gp
  Code repo for "Kernel Interpolation for Scalable Online Gaussian Processes"
  ☆64Updated 4 years ago
• sandialabs / pyapprox
  Flexible and efficient tools for high-dimensional approximation, scientific machine learning and uncertainty quantification.
  ☆63Updated this week
• sydney-machine-learning / Bayesianneuralnetworks-MCMC-tutorial
  Bayesian neural networks via MCMC: tutorial
  ☆57Updated 9 months ago
• andreikitaitsev / SymINDy
  Symbolic Identification of Non-linear Dynamics. The method generalizes the SINDy algorithm by combining sparse and genetic-programming-ba…
  ☆76Updated 2 years ago
• cornellius-gp / linear_operator
  A LinearOperator implementation to wrap the numerical nuts and bolts of GPyTorch
  ☆112Updated 4 months ago