Alternatives and similar repositories for Bayesian-Filtering

Users that are interested in Bayesian-Filtering are comparing it to the libraries listed below

• AaltoML / IHGP
  Infinite-horizon Gaussian processes
  ☆33Updated 4 years ago
• sorooshafiee / WKF
  ☆15Updated 6 years ago
• EEA-sensors / Bayesian-Filtering-and-Smoothing
  Companion Matlab and Python codes for the book Bayesian Filtering and Smoothing by Simo Särkkä and Lennart Svensson
  ☆75Updated last year
• cvxgrp / auto_ks
  Repository for "Fitting a Kalman Smoother to Data"
  ☆59Updated last year
• erichanslee / GP_Derivatives
  Scalable Gaussian Process Regression with Derivatives
  ☆37Updated 6 years ago
• EEA-sensors / parallel-non-linear-gaussian-smoothers
  Companion code in JAX for the paper Parallel Iterated Extended and Sigma-Point Kalman Smoothers.
  ☆27Updated last year
• linesd / SSGPR
  Sparse Spectrum Gaussian Process Regression
  ☆23Updated 5 years ago
• wjmaddox / online_gp
  Code repo for "Kernel Interpolation for Scalable Online Gaussian Processes"
  ☆64Updated 4 years ago
• tingiskhan / pyfilter
  Particle filtering and sequential parameter inference in Python
  ☆83Updated 2 years ago
• thangbui / streaming_sparse_gp
  Streaming sparse Gaussian process approximations
  ☆67Updated 2 years ago
• jnez71 / kalmaNN
  Extended Kalman filter for training neural-networks
  ☆93Updated 4 years ago
• alshedivat / gpml
  An up-to-date version of GPML library.
  ☆38Updated 6 years ago
• cvxgrp / dmcp
  A CVXPY extension for multi-convex programming
  ☆46Updated 2 years ago
• jacobnzw / SSMToybox
  Nonlinear Sigma-Point Kalman Filters based on Bayesian Quadrature
  ☆13Updated 4 years ago
• AaltoML / kalman-jax
  Approximate inference for Markov Gaussian processes using iterated Kalman smoothing, in JAX
  ☆100Updated 2 years ago
• manschuer / SRGP
  stochastic recursive Gaussian Process (SRGP)
  ☆20Updated 4 years ago
• jerkern / pyParticleEst
  Python Library for Particle based estimation methods
  ☆63Updated 6 years ago
• StanfordASL / SNDL
  Stabilizable Nonlinear Dynamics Learning
  ☆22Updated 5 years ago
• zgbkdlm / ssdgp
  State-space deep Gaussian processes in Python and Matlab
  ☆30Updated 3 years ago
• AaltoML / BayesNewton
  Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's method.
  ☆235Updated last year
• thangbui / sparseGP_powerEP
  Unifying sparse approximations for Gaussian process regression and classification, using Power EP
  ☆22Updated 8 years ago
• EEA-sensors / sequential-parallelization-examples
  This is a collection of code samples aimed at illustrating temporal parallelization methods for sequential data.
  ☆33Updated last year
• MarcoTodescato / Efficient-GP-Regression-via-Kalman-Filtering
  Code to implement efficient spatio-temporal Gaussian Process regression via iterative Kalman Filtering. KF is used to resolve the tempora…
  ☆40Updated 7 years ago
• grasool / Gaussian-Processes
  Introduction to Gaussian Processes
  ☆29Updated 7 years ago
• boisgera / control-engineering-with-python
  Control Engineering with Python
  ☆72Updated 3 months ago
• st-- / interactive-gp-visualization
  Interactive visualization of Gaussian processes
  ☆171Updated 2 years ago
• VBayesLab / VBLab
  Official documentation
  ☆30Updated 4 years ago
• agijsberts / ssgpr
  Batch and incremental Sparse Spectrum Gaussian Process for Regression
  ☆10Updated 4 years ago
• decargroup / pykoop
  Koopman operator identification library in Python, compatible with `scikit-learn`
  ☆85Updated last month
• oxfordcontrol / Bayesian-Optimization
  Reference implementation of Optimistic Expected Improvement.
  ☆49Updated 5 years ago