Alternatives and similar repositories for GPfY

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

• pnkraemer / tornadox
  Probabilistic ODE solvers are fun, but are they fast? See also: https://github.com/pnkraemer/probdiffeq for JAX code or https://github.c…
  ☆21Updated last year
• ssm-jax / ssm-book
  Interactive textbook on state space models
  ☆12Updated 3 years ago
• jejjohnson / gp_model_zoo
  Literature and light wrappers for gaussian process models.
  ☆47Updated 4 years ago
• pnkraemer / probfindiff
  Probabilistic numerical finite differences. Compute finite difference weights and differentiation matrices on scattered data sites and wi…
  ☆11Updated 2 years ago
• spdes / chirpgp
  Chirp instantaneous frequency estimation using stochastic differential equation Gaussian processes
  ☆13Updated last year
• dirmeier / ramsey
  Probabilistic deep learning using JAX
  ☆15Updated 10 months ago
• AaltoML / spatio-temporal-GPs
  Code for NeurIPS 2021 paper 'Spatio-Temporal Variational Gaussian Processes'
  ☆46Updated 4 years ago
• EEA-sensors / sqrt-parallel-smoothers
  A generic library for linear and non-linear Gaussian smoothing problems. The code leverages JAX and implements several linearization algo…
  ☆12Updated last year
• adonath / gmmx
  Gaussian Mixture Models in Jax
  ☆23Updated 5 months ago
• aterenin / SparseGPAX
  An ultra-lightweight JAX implementation of sparse Gaussian processes via pathwise sampling.
  ☆21Updated 4 years ago
• vr308 / Generalised-Gaussian-Processes
  Fully Bayesian Inference in GPs - Gaussian and Generic Likelihoods
  ☆22Updated 2 years ago
• secondmind-labs / markovflow
  A Tensorflow based library for Time Series Modelling with Gaussian Processes
  ☆32Updated last year
• ylefay / bayesianSDEsolver
  Efficient SDE samplers including Gaussian-based probabilistic solvers. Written in JAX.
  ☆10Updated 10 months ago
• wesselb / lab
  A generic interface for linear algebra backends
  ☆75Updated last month
• secondmind-labs / GPflux
  Deep GPs built on top of TensorFlow/Keras and GPflow
  ☆127Updated last year
• wesselb / gpar
  Implementation of the Gaussian Process Autoregressive Regression Model
  ☆68Updated 11 months ago
• wesselb / mlkernels
  Kernels, the machine learning ones
  ☆14Updated 2 years ago
• jeremiecoullon / SGMCMCJax
  Lightweight library of stochastic gradient MCMC algorithms written in JAX.
  ☆105Updated 2 years ago
• AdrienCorenflos / particle_mala
  Gradient-informed particle MCMC methods
  ☆12Updated last year
• SamDuffield / mocat
  All things Monte Carlo, written in JAX.
  ☆32Updated 2 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
• timweiland / gp-fvm
  Probabilistic Finite Volume Method based on Affine Gaussian Process inference
  ☆11Updated last year
• wesselb / neuralprocesses
  A framework for composing Neural Processes in Python
  ☆89Updated last year
• wesselb / stheno
  Gaussian process modelling in Python
  ☆226Updated last year
• JonathanWenger / itergp
  IterGP: Computation-Aware Gaussian Process Inference (NeurIPS 2022)
  ☆43Updated 2 years ago
• AaltoML / hilbert-gp
  Codes for Hilbert space reduced-rank GP regression
  ☆14Updated 6 years ago
• wesselb / varz
  Painless optimisation of constrained variables in AutoGrad, TensorFlow, PyTorch, and JAX
  ☆23Updated 2 years ago
• martiningram / jax_advi
  ☆16Updated 8 months 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 last year
• markusheinonen / adaptivegp
  Fully nonstationary, heteroscedastic GP for Matlab
  ☆16Updated last year