jwangjie / Gaussian-Process-Regression-Tutorial

Related projects: ⓘ

• GAMES-UChile / mogptk
  Multi-Output Gaussian Process Toolkit
  ☆161Updated 5 months ago
• jwangjie / gpytorch
  A highly efficient and modular implementation of Gaussian Processes in PyTorch
  ☆16Updated 4 years ago
• BethanyL / DeepKoopman
  neural networks to learn Koopman eigenfunctions
  ☆364Updated 5 months ago
• nchopin / particles
  Sequential Monte Carlo in python
  ☆395Updated 2 weeks ago
• Harry24k / bayesian-neural-network-pytorch
  PyTorch implementation of bayesian neural network [torchbnn]
  ☆476Updated last month
• IntelLabs / bayesian-torch
  A library for Bayesian neural network layers and uncertainty estimation in Deep Learning extending the core of PyTorch
  ☆509Updated 7 months ago
• dynamicslab / pykoopman
  A package for computing data-driven approximations to the Koopman operator.
  ☆293Updated last month
• mksadoughi / Multi-output-Gaussian-Process
  ☆12Updated 5 years ago
• coursekevin / svise
  Accompanying code for "State Estimation of a Physical System without Governing Equations"
  ☆73Updated 2 months ago
• JaxGaussianProcesses / GPJax
  Gaussian processes in JAX.
  ☆436Updated last week
• gdroguski / GaussianProcesses
  Python3 project applying Gaussian process regression for forecasting stock trends
  ☆145Updated 6 years ago
• SheffieldML / PyDeepGP
  Deep Gaussian Processes in Python
  ☆230Updated 3 years ago
• dfm / gp
  A tutorial about Gaussian process regression
  ☆183Updated 4 years ago
• Ulti-Dreisteine / gaussian-process-regression
  高斯过程回归
  ☆73Updated 2 years ago
• SheffieldML / GPy
  Gaussian processes framework in python
  ☆2,011Updated 2 weeks ago
• kpchamp / SindyAutoencoders
  ☆327Updated 2 years ago
• AdamCobb / hamiltorch
  PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC) and inference in Bayesian neural networks
  ☆407Updated 3 weeks ago
• PyDMD / PyDMD
  Python Dynamic Mode Decomposition
  ☆859Updated last month
• AaltoML / SDE
  Example codes for the book Applied Stochastic Differential Equations
  ☆174Updated 3 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…
  ☆109Updated 2 years ago
• sbi-dev / sbi
  Simulation-based inference toolkit
  ☆572Updated last week
• TyXe-BDL / TyXe
  ☆144Updated 2 years ago
• deeptime-ml / deeptime
  Python library for analysis of time series data including dimensionality reduction, clustering, and Markov model estimation
  ☆747Updated 2 months ago
• helange23 / from_fourier_to_koopman
  Linear and non-linear spectral forecasting algorithms
  ☆131Updated 3 years ago
• cagrell / gp_constr
  Python model for constrained GP
  ☆23Updated 3 years ago
• Magica-Chen / gptp_multi_output
  multivariate Gaussian process regression and multivariate Student-t process regression
  ☆65Updated 3 years ago
• secondmind-labs / trieste
  A Bayesian optimization toolbox built on TensorFlow
  ☆217Updated this week
• KrisNguyen135 / bayesian-optimization-in-action
  Source code for Bayesian Optimization in Action, published by Manning
  ☆69Updated last year
• uber-research / TuRBO
  ☆181Updated last month
• cornellius-gp / gpytorch
  A highly efficient implementation of Gaussian Processes in PyTorch
  ☆3,531Updated last week