Alternatives and similar repositories for rebayes:

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

• blackjax-devs / sampling-book
  Tutorials and sampling algorithm comparisons
  ☆74Updated this week
• EEA-sensors / sequential-parallelization-examples
  This is a collection of code samples aimed at illustrating temporal parallelization methods for sequential data.
  ☆31Updated last year
• probml / JSL
  Jax SSM Library
  ☆49Updated 2 years ago
• vincentblot28 / conformalized_gp
  ☆48Updated 3 months ago
• lindermanlab / ssm-jax
  Bayesian learning and inference for state space models (SSMs) using Google Research's JAX as a backend
  ☆58Updated 10 months ago
• acerbilab / pyvbmc
  PyVBMC: Variational Bayesian Monte Carlo algorithm for posterior and model inference in Python
  ☆117Updated 2 months ago
• wesselb / lab
  A generic interface for linear algebra backends
  ☆73Updated last month
• probml / bandits
  Bayesian Bandits
  ☆68Updated last year
• probml / sts-jax
  Structural Time Series in JAX
  ☆189Updated 11 months ago
• gerdm / bayes
  Neat Bayesian machine learning examples
  ☆55Updated 3 months ago
• jeremiecoullon / SGMCMCJax
  Lightweight library of stochastic gradient MCMC algorithms written in JAX.
  ☆103Updated last year
• g-benton / Volt
  Public Implementation of Volatility Based Kernels and Moving Average Means for Accurate Forecasting with Gaussian Processes
  ☆48Updated 2 years ago
• AaltoML / kalman-jax
  Approximate inference for Markov Gaussian processes using iterated Kalman smoothing, in JAX
  ☆99Updated last year
• vr308 / Generalised-Gaussian-Processes
  Fully Bayesian Inference in GPs - Gaussian and Generic Likelihoods
  ☆22Updated last year
• aterenin / SparseGPAX
  An ultra-lightweight JAX implementation of sparse Gaussian processes via pathwise sampling.
  ☆22Updated 4 years ago
• canyon289 / ssm_book_club
  ☆17Updated 2 years ago
• amzn / orthogonal-additive-gaussian-processes
  Light-weighted code for Orthogonal Additive Gaussian Processes
  ☆42Updated 8 months ago
• probabilisticai / probai-2023
  Materials of the Nordic Probabilistic AI School 2023.
  ☆91Updated last year
• tgcsaba / GPSig
  Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances
  ☆47Updated last year
• wesselb / gpar
  Implementation of the Gaussian Process Autoregressive Regression Model
  ☆65Updated 3 months ago
• jax-ml / bayeux
  State of the art inference for your bayesian models.
  ☆209Updated last week
• secondmind-labs / markovflow
  A Tensorflow based library for Time Series Modelling with Gaussian Processes
  ☆30Updated 9 months ago
• pierresegonne / VINF
  Repository for DTU Special Course, focusing on Variational Inference using Normalizing Flows (VINF). Supervised by Michael Riis Andersen
  ☆25Updated 4 years ago
• pymc-devs / pymc-extras
  Powerful add-ons for PyMC
  ☆98Updated this week
• AaltoML / BayesNewton
  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
• JTT94 / filterflow
  Extensible Tensorflow library for differentiable particle filtering. ICML 2021.
  ☆42Updated 2 years ago
• AaltoML / spatio-temporal-GPs
  Code for NeurIPS 2021 paper 'Spatio-Temporal Variational Gaussian Processes'
  ☆47Updated 3 years ago
• AdrienCorenflos / jax-workshop
  JAX workshop for beginners
  ☆8Updated 3 months ago
• JonathanWenger / itergp
  IterGP: Computation-Aware Gaussian Process Inference (NeurIPS 2022)
  ☆41Updated 2 years ago
• geraschenko / gmrfs
  Gaussian Markov Random Fields (GMRFs) and Integrated Nested Laplace Approximation (INLA)
  ☆20Updated last year