Alternatives and similar repositories for GPflux:

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

• secondmind-labs / trieste
  A Bayesian optimization toolbox built on TensorFlow
  ☆229Updated 2 weeks ago
• j-wilson / GPflowSampling
  Code for efficiently sampling functions from GP(flow) posteriors
  ☆72Updated 4 years ago
• jeremiecoullon / SGMCMCJax
  Lightweight library of stochastic gradient MCMC algorithms written in JAX.
  ☆102Updated last year
• 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
• wesselb / stheno
  Gaussian process modelling in Python
  ☆222Updated 3 months ago
• amzn / orthogonal-additive-gaussian-processes
  Light-weighted code for Orthogonal Additive Gaussian Processes
  ☆42Updated 8 months ago
• TyXe-BDL / TyXe
  ☆151Updated 2 years ago
• hughsalimbeni / bayesian_benchmarks
  A community repository for benchmarking Bayesian methods
  ☆110Updated 3 years ago
• JaxGaussianProcesses / GPJax
  Gaussian processes in JAX and Flax.
  ☆496Updated this week
• secondmind-labs / markovflow
  A Tensorflow based library for Time Series Modelling with Gaussian Processes
  ☆30Updated 9 months ago
• AaltoML / kalman-jax
  Approximate inference for Markov Gaussian processes using iterated Kalman smoothing, in JAX
  ☆98Updated last year
• UCL-SML / Doubly-Stochastic-DGP
  Deep Gaussian Processes with Doubly Stochastic Variational Inference
  ☆150Updated 6 years ago
• cornellius-gp / linear_operator
  A LinearOperator implementation to wrap the numerical nuts and bolts of GPyTorch
  ☆107Updated last month
• wesselb / gpar
  Implementation of the Gaussian Process Autoregressive Regression Model
  ☆65Updated 2 months ago
• markvdw / RobustGP
  Robust initialisation of inducing points in sparse variational GP regression models.
  ☆33Updated 2 years ago
• wesselb / neuralprocesses
  A framework for composing Neural Processes in Python
  ☆84Updated 3 months ago
• xwinxu / bayeSDE
  Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"
  ☆169Updated 3 years ago
• wesselb / lab
  A generic interface for linear algebra backends
  ☆73Updated last month
• GAMES-UChile / mogptk
  Multi-Output Gaussian Process Toolkit
  ☆170Updated 11 months ago
• cooper-org / cooper
  A general-purpose, deep learning-first library for constrained optimization in PyTorch
  ☆115Updated last week
• karalets / TyXe
  Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)
  ☆42Updated 3 years ago
• jejjohnson / gp_model_zoo
  Literature and light wrappers for gaussian process models.
  ☆45Updated 3 years ago
• jacobjinkelly / easy-neural-ode
  Code for the paper "Learning Differential Equations that are Easy to Solve"
  ☆279Updated 3 years ago
• danielward27 / flowjax
  ☆154Updated last month
• sbi-benchmark / sbibm
  Simulation-based inference benchmark
  ☆96Updated 2 months ago
• dfm / tinygp
  The tiniest of Gaussian Process libraries
  ☆306Updated this week
• willieneis / bayesian-algorithm-execution
  Bayesian algorithm execution (BAX)
  ☆49Updated 3 years ago
• jmaronas / TGP.pytorch
  Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021
  ☆24Updated 2 years ago
• hegdepashupati / differential-dgp
  Implementation of stochastic variational inference for differentially deep gaussian processes
  ☆15Updated 6 years ago
• gpapamak / snl
  Sequential Neural Likelihood
  ☆41Updated 5 years ago