Alternatives and similar repositories for rebayes

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

• probml / JSL
  Jax SSM Library
  ☆48Updated 2 years ago
• acerbilab / pyvbmc
  PyVBMC: Variational Bayesian Monte Carlo algorithm for posterior and model inference in Python
  ☆122Updated 3 weeks ago
• probml / sts-jax
  Structural Time Series in JAX
  ☆200Updated last year
• blackjax-devs / sampling-book
  Tutorials and sampling algorithm comparisons
  ☆77Updated 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.
  ☆239Updated last year
• jeremiecoullon / SGMCMCJax
  Lightweight library of stochastic gradient MCMC algorithms written in JAX.
  ☆105Updated 2 years ago
• JonathanWenger / itergp
  IterGP: Computation-Aware Gaussian Process Inference (NeurIPS 2022)
  ☆42Updated 2 years ago
• AaltoML / kalman-jax
  Approximate inference for Markov Gaussian processes using iterated Kalman smoothing, in JAX
  ☆102Updated 2 years ago
• lindermanlab / ssm-jax
  Bayesian learning and inference for state space models (SSMs) using Google Research's JAX as a backend
  ☆60Updated last year
• wesselb / lab
  A generic interface for linear algebra backends
  ☆74Updated 7 months ago
• gerdm / bayes
  Neat Bayesian machine learning examples
  ☆58Updated this week
• canyon289 / ssm_book_club
  ☆18Updated 2 years ago
• aterenin / SparseGPAX
  An ultra-lightweight JAX implementation of sparse Gaussian processes via pathwise sampling.
  ☆22Updated 4 years ago
• 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
• karalets / TyXe
  Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)
  ☆42Updated 4 years ago
• secondmind-labs / markovflow
  A Tensorflow based library for Time Series Modelling with Gaussian Processes
  ☆32Updated last year
• tgcsaba / GPSig
  Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances
  ☆48Updated 2 years ago
• wesselb / gpar
  Implementation of the Gaussian Process Autoregressive Regression Model
  ☆68Updated 9 months ago
• probml / bandits
  Bayesian Bandits
  ☆68Updated 2 years ago
• vr308 / Generalised-Gaussian-Processes
  Fully Bayesian Inference in GPs - Gaussian and Generic Likelihoods
  ☆22Updated 2 years ago
• jax-ml / bayeux
  State of the art inference for your bayesian models.
  ☆226Updated 5 months ago
• cambridge-mlg / sgd-gp
  Public code for running Stochastic Gradient Descent on GPs.
  ☆39Updated 6 months ago
• TyXe-BDL / TyXe
  ☆154Updated 3 years ago
• RaulPL / awesome-gaussian-processes
  A curated list of resources for learning Gaussian Processes
  ☆41Updated 4 years ago
• vincentblot28 / conformalized_gp
  ☆48Updated 9 months ago
• AaltoML / spatio-temporal-GPs
  Code for NeurIPS 2021 paper 'Spatio-Temporal Variational Gaussian Processes'
  ☆47Updated 3 years ago
• pnkraemer / probdiffeq
  Probabilistic solvers for differential equations in JAX. Adaptive ODE solvers with calibration, state-space model factorisations, and cus…
  ☆53Updated last month
• j-wilson / GPflowSampling
  Code for efficiently sampling functions from GP(flow) posteriors
  ☆73Updated 4 years ago
• dkobak / high-dim-ridge
  The optimal ridge penalty for real-world high-dimensional data can be zero or negative due to the implicit ridge regularization
  ☆31Updated 3 years ago
• gerdm / rebayes-mini
  Minimalist version of probml/rebayes
  ☆10Updated last month