jwangjie / Gaussian-Process-Regression-TutorialLinks
An Intuitive Tutorial to Gaussian Processes Regression
☆637Updated 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:
- Multi-Output Gaussian Process Toolkit☆176Updated 2 months ago
- PyTorch implementation of bayesian neural network [torchbnn]☆539Updated last year
- A meta repository pointing to the other repositories where the implementation of the supplementary examples for our tutorial "Hands-on Ba…☆134Updated 3 years ago
- neural networks to learn Koopman eigenfunctions☆422Updated last year
- Accompanying code for "State Estimation of a Physical System without Governing Equations"☆89Updated last year
- A library for Bayesian neural network layers and uncertainty estimation in Deep Learning extending the core of PyTorch☆615Updated 4 months ago
- A package for computing data-driven approximations to the Koopman operator.☆374Updated 9 months ago
- ☆15Updated 6 years ago
- 高斯过程回归☆83Updated 3 years ago
- Bayesian neural networks via MCMC: tutorial☆58Updated 10 months ago
- Source code for Bayesian Optimization in Action, published by Manning☆104Updated 2 years ago
- multivariate Gaussian process regression and multivariate Student-t process regression☆76Updated 4 years ago
- Source Code for 'Bayesian Optimization' by Peng Liu☆30Updated 2 years ago
- A general-purpose Python package for Koopman theory using deep learning.☆106Updated 6 months ago
- Streaming sparse Gaussian process approximations☆67Updated 2 years ago
- Python model for constrained GP☆25Updated 4 years ago
- Sequential Monte Carlo in python☆465Updated 3 weeks ago
- A library for Koopman Neural Operator with Pytorch.☆302Updated 10 months ago
- GPz 2.0: Heteroscedastic Gaussian processes for uncertain and incomplete data☆49Updated 4 years ago
- IPython notebooks with demo code intended as a companion to the book "Data-Driven Science and Engineering: Machine Learning, Dynamical Sy…☆151Updated 3 years ago
- Gaussian Process Regression Techniques - The source code corresponding to the Ph.D. thesis.☆72Updated 8 years ago
- A Python package to learn the Koopman operator.☆61Updated 9 months ago
- Regression datasets from the UCI repository with standardized test-train splits.☆47Updated 3 years ago
- Companion Matlab and Python codes for the book Bayesian Filtering and Smoothing by Simo Särkkä and Lennart Svensson☆76Updated last year
- ☆366Updated 3 years ago
- ☆88Updated 2 years ago
- UQpy (Uncertainty Quantification with python) is a general purpose Python toolbox for modeling uncertainty in physical and mathematical s…☆323Updated last week
- The only guide you need to learn everything about GMM☆128Updated 8 months ago
- Toy models, experiments and random notes on machine learning and deep learning.☆128Updated 10 months ago
- Empowering extended Kalman filter (EKF) with Sparse Identification of Nonlinear Dynamics (SINDy)☆62Updated 4 months ago