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 3 months ago
• IntelLabs / bayesian-torch
  A library for Bayesian neural network layers and uncertainty estimation in Deep Learning extending the core of PyTorch
  ☆622Updated 5 months ago
• Harry24k / bayesian-neural-network-pytorch
  PyTorch implementation of bayesian neural network [torchbnn]
  ☆542Updated last year
• dynamicslab / pykoopman
  A package for computing data-driven approximations to the Koopman operator.
  ☆376Updated 10 months ago
• Magica-Chen / gptp_multi_output
  multivariate Gaussian process regression and multivariate Student-t process regression
  ☆75Updated 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…
  ☆135Updated 3 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
  ☆103Updated 2 years ago
• sydney-machine-learning / Bayesianneuralnetworks-MCMC-tutorial
  Bayesian neural networks via MCMC: tutorial
  ☆58Updated 10 months ago
• Ulti-Dreisteine / gaussian-process-regression
  高斯过程回归
  ☆84Updated 3 years ago
• BethanyL / DeepKoopman
  neural networks to learn Koopman eigenfunctions
  ☆428Updated last year
• coursekevin / svise
  Accompanying code for "State Estimation of a Physical System without Governing Equations"
  ☆89Updated last year
• nchopin / particles
  Sequential Monte Carlo in python
  ☆466Updated last week
• Apress / Bayesian-optimization
  Source Code for 'Bayesian Optimization' by Peng Liu
  ☆30Updated 2 years ago
• SURGroup / UQpy
  UQpy (Uncertainty Quantification with python) is a general purpose Python toolbox for modeling uncertainty in physical and mathematical s…
  ☆323Updated 3 weeks ago
• Koopman-Laboratory / KoopmanLab
  A library for Koopman Neural Operator with Pytorch.
  ☆302Updated 11 months ago
• kpchamp / SindyAutoencoders
  ☆368Updated 3 years ago
• thangbui / streaming_sparse_gp
  Streaming sparse Gaussian process approximations
  ☆68Updated 2 years ago
• GaloisInc / dlkoopman
  A general-purpose Python package for Koopman theory using deep learning.
  ☆108Updated 7 months ago
• dynamicslab / SINDy-PI
  SINDy-PI: A Robust Algorithm for Parallel Implicit Sparse Identification of Nonlinear Dynamics
  ☆152Updated 4 years ago
• Crunch-UQ4MI / neuraluq
  ☆189Updated 5 months ago
• french-paragon / BayesianMnist
  A hello world Bayesian Neural Network project on MNIST
  ☆47Updated 3 years ago
• borgwang / toys
  Toy models, experiments and random notes on machine learning and deep learning.
  ☆128Updated 11 months ago
• SheffieldML / PyDeepGP
  Deep Gaussian Processes in Python
  ☆236Updated 4 years ago
• OxfordML / GPz
  GPz 2.0: Heteroscedastic Gaussian processes for uncertain and incomplete data
  ☆48Updated 4 years ago
• PyDMD / PyDMD
  Python Dynamic Mode Decomposition
  ☆1,034Updated last month
• clegaard / deep_learning_for_dynamical_systems
  ☆88Updated 2 years ago
• ContiPaolo / EKF-SINDy
  Empowering extended Kalman filter (EKF) with Sparse Identification of Nonlinear Dynamics (SINDy)
  ☆63Updated 4 months ago