jwangjie / Gaussian-Process-Regression-TutorialLinks
An Intuitive Tutorial to Gaussian Processes Regression
☆647Updated 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☆176Updated 4 months ago
- multivariate Gaussian process regression and multivariate Student-t process regression☆75Updated 4 years ago
- 高斯过程回归☆84Updated 3 years ago
- A library for Bayesian neural network layers and uncertainty estimation in Deep Learning extending the core of PyTorch☆626Updated 6 months ago
- Accompanying code for "State Estimation of a Physical System without Governing Equations"☆90Updated last year
- PyTorch implementation of bayesian neural network [torchbnn]☆545Updated last year
- Bayesian neural networks via MCMC: tutorial☆58Updated last year
- A package for computing data-driven approximations to the Koopman operator.☆387Updated 11 months ago
- Streaming sparse Gaussian process approximations☆68Updated 3 years 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…☆136Updated 3 years ago
- Python model for constrained GP☆26Updated 4 years ago
- Source Code for 'Bayesian Optimization' by Peng Liu☆30Updated 2 years ago
- neural networks to learn Koopman eigenfunctions☆439Updated last year
- Sparse Spectrum Gaussian Process Regression☆23Updated 5 years ago
- Gaussian Process Regression Techniques - The source code corresponding to the Ph.D. thesis.☆71Updated 8 years ago
- A general-purpose Python package for Koopman theory using deep learning.☆110Updated last month
- A library for Koopman Neural Operator with Pytorch.☆306Updated last year
- Source code for Bayesian Optimization in Action, published by Manning☆103Updated 2 years ago
- Sequential Monte Carlo in python☆471Updated 2 weeks ago
- The only guide you need to learn everything about GMM☆130Updated 10 months ago
- GPz 2.0: Heteroscedastic Gaussian processes for uncertain and incomplete data☆49Updated 4 years ago
- A Python package to learn the Koopman operator.☆63Updated this week
- Deep Gaussian Processes in Python☆236Updated 4 years ago
- Companion Matlab and Python codes for the book Bayesian Filtering and Smoothing by Simo Särkkä and Lennart Svensson☆78Updated last year
- Neural Extended Kalman Filters☆16Updated 2 years ago
- ☆139Updated 11 months ago
- Collection of Monte Carlo (MC) and Markov Chain Monte Carlo (MCMC) algorithms applied on simple examples.☆382Updated 7 years ago
- UQpy (Uncertainty Quantification with python) is a general purpose Python toolbox for modeling uncertainty in physical and mathematical s…☆329Updated 2 months ago