sursu / Bayesian-FilteringLinks
Bayesian Filtering & Smoothing demos
☆19Updated 5 years ago
Alternatives and similar repositories for Bayesian-Filtering
Users that are interested in Bayesian-Filtering are comparing it to the libraries listed below
Sorting:
- Companion Matlab and Python codes for the book Bayesian Filtering and Smoothing by Simo Särkkä and Lennart Svensson☆78Updated last year
- Companion code in JAX for the paper Parallel Iterated Extended and Sigma-Point Kalman Smoothers.☆27Updated last year
- ☆16Updated 6 years ago
- Infinite-horizon Gaussian processes☆33Updated 4 years ago
- Scalable Gaussian Process Regression with Derivatives☆38Updated 6 years ago
- Repository for "Fitting a Kalman Smoother to Data"☆60Updated last year
- Particle filtering and sequential parameter inference in Python☆84Updated 2 years ago
- Sparse Spectrum Gaussian Process Regression☆23Updated 5 years ago
- Extended Kalman filter for training neural-networks☆94Updated 4 years ago
- Streaming sparse Gaussian process approximations☆67Updated 2 years ago
- Code repo for "Kernel Interpolation for Scalable Online Gaussian Processes"☆64Updated 4 years ago
- Approximate inference for Markov Gaussian processes using iterated Kalman smoothing, in JAX☆100Updated 2 years ago
- ☆137Updated 10 months ago
- An up-to-date version of GPML library.☆37Updated 6 years ago
- Nonlinear Sigma-Point Kalman Filters based on Bayesian Quadrature☆12Updated 4 years ago
- Control Engineering with Python☆73Updated 4 months ago
- Stabilizable Nonlinear Dynamics Learning☆22Updated 5 years ago
- Unifying sparse approximations for Gaussian process regression and classification, using Power EP☆22Updated 8 years ago
- Koopman operator identification library in Python, compatible with `scikit-learn`☆84Updated 2 months ago
- Official documentation☆30Updated 4 years ago
- Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's method.☆236Updated last year
- Interactive visualization of Gaussian processes☆172Updated 2 years ago
- This is a collection of code samples aimed at illustrating temporal parallelization methods for sequential data.☆33Updated 2 years ago
- GPz 2.0: Heteroscedastic Gaussian processes for uncertain and incomplete data☆48Updated 4 years ago
- Python Library for Particle based estimation methods☆63Updated 6 years ago
- stochastic recursive Gaussian Process (SRGP)☆20Updated 4 years ago
- Online variational GPs☆37Updated 2 years ago
- APPM 5630 at CU Boulder☆51Updated last month
- State-space deep Gaussian processes in Python and Matlab☆30Updated 3 years ago
- Provides a heteroscedastic noise latent for a sparse variational Gaussian process using GPflow☆13Updated 4 years ago