Alternatives and similar repositories for Gaussian-Process-Regression-Tutorial

Users that are interested in Gaussian-Process-Regression-Tutorial are comparing it to the libraries listed below

• jwangjie / gpytorch
  A highly efficient and modular implementation of Gaussian Processes in PyTorch
  ☆16Updated 5 years ago
• GAMES-UChile / mogptk
  Multi-Output Gaussian Process Toolkit
  ☆175Updated 2 months 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…
  ☆133Updated 3 years ago
• IntelLabs / bayesian-torch
  A library for Bayesian neural network layers and uncertainty estimation in Deep Learning extending the core of PyTorch
  ☆613Updated 3 months ago
• dynamicslab / pykoopman
  A package for computing data-driven approximations to the Koopman operator.
  ☆373Updated 9 months ago
• Ulti-Dreisteine / gaussian-process-regression
  高斯过程回归
  ☆82Updated 3 years ago
• Harry24k / bayesian-neural-network-pytorch
  PyTorch implementation of bayesian neural network [torchbnn]
  ☆539Updated last year
• BethanyL / DeepKoopman
  neural networks to learn Koopman eigenfunctions
  ☆421Updated last year
• coursekevin / svise
  Accompanying code for "State Estimation of a Physical System without Governing Equations"
  ☆88Updated last year
• Magica-Chen / gptp_multi_output
  multivariate Gaussian process regression and multivariate Student-t process regression
  ☆76Updated 4 years ago
• mksadoughi / Multi-output-Gaussian-Process
  ☆15Updated 6 years ago
• cagrell / gp_constr
  Python model for constrained GP
  ☆25Updated 4 years ago
• KrisNguyen135 / bayesian-optimization-in-action
  Source code for Bayesian Optimization in Action, published by Manning
  ☆105Updated 2 years ago
• sydney-machine-learning / Bayesianneuralnetworks-MCMC-tutorial
  Bayesian neural networks via MCMC: tutorial
  ☆57Updated 9 months ago
• Koopman-Laboratory / KoopmanLab
  A library for Koopman Neural Operator with Pytorch.
  ☆298Updated 10 months ago
• nchopin / particles
  Sequential Monte Carlo in python
  ☆462Updated this week
• thangbui / streaming_sparse_gp
  Streaming sparse Gaussian process approximations
  ☆67Updated 2 years ago
• borgwang / toys
  Toy models, experiments and random notes on machine learning and deep learning.
  ☆128Updated 10 months ago
• Apress / Bayesian-optimization
  Source Code for 'Bayesian Optimization' by Peng Liu
  ☆30Updated 2 years ago
• GaloisInc / dlkoopman
  A general-purpose Python package for Koopman theory using deep learning.
  ☆106Updated 6 months ago
• treforevans / uci_datasets
  Regression datasets from the UCI repository with standardized test-train splits.
  ☆47Updated 3 years ago
• OxfordML / GPz
  GPz 2.0: Heteroscedastic Gaussian processes for uncertain and incomplete data
  ☆49Updated 4 years ago
• Zymrael / awesome-neural-ode
  A collection of resources regarding the interplay between differential equations, deep learning, dynamical systems, control and numerical…
  ☆1,458Updated 10 months ago
• kpchamp / SindyAutoencoders
  ☆362Updated 3 years ago
• AdamCobb / hamiltorch
  PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC) and inference in Bayesian neural networks
  ☆456Updated 11 months ago
• SheffieldML / PyDeepGP
  Deep Gaussian Processes in Python
  ☆234Updated 4 years ago
• SURGroup / UQpy
  UQpy (Uncertainty Quantification with python) is a general purpose Python toolbox for modeling uncertainty in physical and mathematical s…
  ☆323Updated 2 weeks ago
• Machine-Learning-Dynamical-Systems / kooplearn
  A Python package to learn the Koopman operator.
  ☆60Updated 8 months ago
• Crunch-UQ4MI / neuraluq
  ☆184Updated 4 months ago
• TyXe-BDL / TyXe
  ☆151Updated 2 years ago