EEA-sensors / Bayesian-Filtering-and-Smoothing
Companion Matlab and Python codes for the book Bayesian Filtering and Smoothing by Simo Särkkä and Lennart Svensson
☆68Updated last year
Alternatives and similar repositories for Bayesian-Filtering-and-Smoothing:
Users that are interested in Bayesian-Filtering-and-Smoothing are comparing it to the libraries listed below
- Accompanying code for "State Estimation of a Physical System without Governing Equations"☆85Updated 8 months ago
- stochastic recursive Gaussian Process (SRGP)☆20Updated 4 years ago
- Zheng Zhao's doctoral dissertation from Aalto University☆34Updated 2 years ago
- Koopman operator identification library in Python, compatible with `scikit-learn`☆70Updated 4 months ago
- Official documentation☆28Updated 4 years ago
- Companion code in JAX for the paper Parallel Iterated Extended and Sigma-Point Kalman Smoothers.☆26Updated 7 months ago
- Scalable Gaussian Process Regression with Derivatives☆38Updated 6 years ago
- Data-driven dynamical systems toolbox.☆73Updated last month
- State-space deep Gaussian processes in Python and Matlab☆29Updated 2 years ago
- ☆15Updated 8 years ago
- Repository for "Fitting a Kalman Smoother to Data"☆58Updated last year
- Bayesian Filtering & Smoothing demos☆18Updated 5 years ago
- Particle filtering and sequential parameter inference in Python☆79Updated last year
- This is a collection of code samples aimed at illustrating temporal parallelization methods for sequential data.☆31Updated last year
- IterGP: Computation-Aware Gaussian Process Inference (NeurIPS 2022)☆40Updated last year
- Approximate inference for Markov Gaussian processes using iterated Kalman smoothing, in JAX☆98Updated last year
- Neural Extended Kalman Filters☆12Updated last year
- Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's method.☆232Updated last year
- A Tensorflow based library for Time Series Modelling with Gaussian Processes☆30Updated 8 months ago
- Streaming sparse Gaussian process approximations☆64Updated 2 years ago
- GPz 2.0: Heteroscedastic Gaussian processes for uncertain and incomplete data☆49Updated 3 years ago
- Taylor moment expansion in Python (JaX and SymPy) and Matlab☆11Updated 4 months ago
- ☆20Updated last year
- Code to implement efficient spatio-temporal Gaussian Process regression via iterative Kalman Filtering. KF is used to resolve the tempora…☆38Updated 6 years ago
- Nonlinear Sigma-Point Kalman Filters based on Bayesian Quadrature☆13Updated 3 years ago
- Koopman Kernels for Learning Dynamical Systems from Trajectory Data☆24Updated last year
- A Python package to learn the Koopman operator.☆54Updated 4 months ago
- ☆11Updated 2 years ago
- A generic library for linear and non-linear Gaussian smoothing problems. The code leverages JAX and implements several linearization algo…☆12Updated 3 months ago
- Probabilistic solvers for differential equations in JAX. Adaptive ODE solvers with calibration, state-space model factorisations, and cus…☆44Updated this week