Alternatives and similar repositories for pyfilter

Users that are interested in pyfilter are comparing it to the libraries listed below

• cvxgrp / auto_ks
  Repository for "Fitting a Kalman Smoother to Data"
  ☆61Updated last year
• johnhw / pfilter
  Basic Python particle filter
  ☆180Updated 2 years ago
• strongio / torchcast
  Forecasting with PyTorch
  ☆55Updated 2 weeks ago
• AaltoML / kalman-jax
  Approximate inference for Markov Gaussian processes using iterated Kalman smoothing, in JAX
  ☆103Updated 2 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.
  ☆241Updated 2 years ago
• nchopin / particles
  Sequential Monte Carlo in python
  ☆483Updated 3 months ago
• AaltoML / IHGP
  Infinite-horizon Gaussian processes
  ☆33Updated 5 years ago
• pmorenoz / RecyclableGP
  Recyclable Gaussian Processes
  ☆11Updated 3 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
  ☆82Updated this week
• EEA-sensors / sequential-parallelization-examples
  This is a collection of code samples aimed at illustrating temporal parallelization methods for sequential data.
  ☆33Updated 2 years ago
• jerkern / pyParticleEst
  Python Library for Particle based estimation methods
  ☆63Updated 7 years ago
• oseiskar / simdkalman
  Python Kalman filters vectorized as Single Instruction, Multiple Data
  ☆189Updated 2 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
• LCAS / RKN
  ☆47Updated 3 years ago
• wesselb / stheno
  Gaussian process modelling in Python
  ☆226Updated last year
• jamesross2 / Bayesian-HMM
  A non-parametric Bayesian approach to Hidden Markov Models
  ☆87Updated 2 years ago
• helange23 / from_fourier_to_koopman
  Linear and non-linear spectral forecasting algorithms
  ☆139Updated 4 years ago
• wesselb / gpar
  Implementation of the Gaussian Process Autoregressive Regression Model
  ☆71Updated last year
• jacobnzw / SSMToybox
  Nonlinear Sigma-Point Kalman Filters based on Bayesian Quadrature
  ☆12Updated 4 years ago
• fmorenopino / HeterogeneousHMM
  Discrete, Gaussian, and Heterogenous HMM models full implemented in Python. Missing data, Model Selection Criteria (AIC/BIC), and Semi-Su…
  ☆80Updated 2 years ago
• pmorenoz / ContinualGP
  Continual Gaussian Processes
  ☆31Updated 2 years ago
• zgbkdlm / ssdgp
  State-space deep Gaussian processes in Python and Matlab
  ☆30Updated 3 years ago
• pierresegonne / VINF
  Repository for DTU Special Course, focusing on Variational Inference using Normalizing Flows (VINF). Supervised by Michael Riis Andersen
  ☆26Updated 5 years ago
• gerdm / rebayes-mini
  Minimalist version of probml/rebayes
  ☆10Updated 4 months ago
• jgosmann / goppy
  Gaussian Online Processes for Python
  ☆19Updated last year
• tiskw / random-fourier-features
  Implementation of random Fourier features for kernel method, like support vector machine and Gaussian process model
  ☆103Updated last year
• sursu / Bayesian-Filtering
  Bayesian Filtering & Smoothing demos
  ☆19Updated 6 years ago
• OxfordML / GPz
  GPz 2.0: Heteroscedastic Gaussian processes for uncertain and incomplete data
  ☆49Updated 4 years ago
• pmorenoz / HetMOGP
  Heterogeneous Multi-output Gaussian Processes
  ☆54Updated 5 years ago
• cvxgrp / signal-decomposition
  A simple and general framework for signal decomposition
  ☆74Updated last year