jwangjie / Gaussian-Process-Regression-TutorialLinks
An Intuitive Tutorial to Gaussian Processes Regression
☆659Updated last year
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
Sorting:
- A highly efficient and modular implementation of Gaussian Processes in PyTorch☆16Updated 5 years ago
- Multi-Output Gaussian Process Toolkit☆182Updated 6 months ago
- Accompanying code for "State Estimation of a Physical System without Governing Equations"☆93Updated last year
- PyTorch implementation of bayesian neural network [torchbnn]☆553Updated last year
- multivariate Gaussian process regression and multivariate Student-t process regression☆77Updated 3 weeks ago
- ☆15Updated 6 years ago
- A meta repository pointing to the other repositories where the implementation of the supplementary examples for our tutorial "Hands-on Ba…☆139Updated 3 years ago
- Python model for constrained GP☆26Updated 4 years ago
- neural networks to learn Koopman eigenfunctions☆455Updated last year
- A package for computing data-driven approximations to the Koopman operator.☆400Updated last year
- Bayesian neural networks via MCMC: tutorial☆60Updated last year
- Source code for Bayesian Optimization in Action, published by Manning☆107Updated 2 years ago
- 高斯过程回归☆85Updated 3 years ago
- Source Code for 'Bayesian Optimization' by Peng Liu☆30Updated 2 years ago
- Streaming sparse Gaussian process approximations☆69Updated 3 years ago
- Sequential Monte Carlo in python☆474Updated 2 months ago
- Deep Gaussian Processes in Python☆236Updated 4 years ago
- A library for Koopman Neural Operator with Pytorch.☆312Updated last year
- Regression datasets from the UCI repository with standardized test-train splits.☆52Updated 3 years ago
- A hello world Bayesian Neural Network project on MNIST☆51Updated 3 years ago
- A general-purpose Python package for Koopman theory using deep learning.☆116Updated 3 months ago
- Toy models, experiments and random notes on machine learning and deep learning.☆129Updated last year
- UQpy (Uncertainty Quantification with python) is a general purpose Python toolbox for modeling uncertainty in physical and mathematical s…☆340Updated last month
- Companion Matlab and Python codes for the book Bayesian Filtering and Smoothing by Simo Särkkä and Lennart Svensson☆82Updated last year
- Heterogeneous Multi-output Gaussian Processes☆54Updated 5 years ago
- ☆142Updated last year
- Koopman operator identification library in Python, compatible with `scikit-learn`☆101Updated 3 months ago
- PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC) and inference in Bayesian neural networks☆462Updated last year
- GPstuff - Gaussian process models for Bayesian analysis☆175Updated 3 years ago
- A Python package to learn the Koopman operator.☆65Updated this week