Alternatives and similar repositories for adaptivegp

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

• wesselb / gpar
  Implementation of the Gaussian Process Autoregressive Regression Model
  ☆68Updated 10 months ago
• AaltoML / hilbert-gp
  Codes for Hilbert space reduced-rank GP regression
  ☆14Updated 6 years ago
• stefanosele / GPfY
  Gaussian processes with spherical harmonic features in JAX
  ☆15Updated 3 months ago
• secondmind-labs / markovflow
  A Tensorflow based library for Time Series Modelling with Gaussian Processes
  ☆32Updated last year
• sremes / nonstationary-spectral-kernels
  Implementation for Non-stationary Spectral Kernels (NIPS 2017)
  ☆20Updated 5 years ago
• RaulPL / awesome-gaussian-processes
  A curated list of resources for learning Gaussian Processes
  ☆41Updated 4 years ago
• JonathanWenger / itergp
  IterGP: Computation-Aware Gaussian Process Inference (NeurIPS 2022)
  ☆42Updated 2 years ago
• matt-graham / mici
  Manifold Markov chain Monte Carlo methods in Python
  ☆236Updated last week
• sremes / nssm-gp
  Non-stationary spectral mixture kernels implemented in GPflow
  ☆28Updated 7 years ago
• aidanscannell / GPJax
  Minimal Gaussian process library in JAX with a simple (custom) approach to state management.
  ☆12Updated last year
• jejjohnson / gp_model_zoo
  Literature and light wrappers for gaussian process models.
  ☆47Updated 4 years ago
• spdes / chirpgp
  Chirp instantaneous frequency estimation using stochastic differential equation Gaussian processes
  ☆13Updated last year
• secondmind-labs / GPflux
  Deep GPs built on top of TensorFlow/Keras and GPflow
  ☆127Updated last year
• rmgarnett / gpml_extensions
  Provides various extensions to the GPML toolbox for Gaussian process inference in MATLAB.
  ☆34Updated 8 years ago
• OxfordML / GPz
  GPz 2.0: Heteroscedastic Gaussian processes for uncertain and incomplete data
  ☆48Updated 4 years ago
• jejjohnson / uncertain_gps
  Exploring how to to deal with uncertain inputs with gaussian process regression models.
  ☆27Updated 4 years ago
• aterenin / SparseGPAX
  An ultra-lightweight JAX implementation of sparse Gaussian processes via pathwise sampling.
  ☆22Updated 4 years ago
• jajcayn / pygpso
  Gaussian-Processes Surrogate Optimisation in python
  ☆19Updated 4 years ago
• eth-cscs / abcpy
  ABCpy package
  ☆116Updated last year
• IPL-UV / jaxkern
  A lightweight didactic library of kernel methods using the back-end JAX.
  ☆12Updated 2 years ago
• amzn / orthogonal-additive-gaussian-processes
  Light-weighted code for Orthogonal Additive Gaussian Processes
  ☆43Updated last year
• AaltoML / spatio-temporal-GPs
  Code for NeurIPS 2021 paper 'Spatio-Temporal Variational Gaussian Processes'
  ☆47Updated 4 years ago
• PredictiveIntelligenceLab / GP-NODEs
  ☆28Updated 3 years ago
• ssm-jax / ssm-book
  Interactive textbook on state space models
  ☆12Updated 3 years ago
• eigenfoo / littlemcmc
  A lightweight and performant implementation of HMC and NUTS in Python, spun out of the PyMC project.
  ☆58Updated last year
• PredictiveIntelligenceLab / JAX-BO
  ☆30Updated 3 years ago
• maziarraissi / ParametricGP
  Parametric Gaussian Process Regression for Big Data
  ☆45Updated 5 years ago
• j-wilson / GPflowSampling
  Code for efficiently sampling functions from GP(flow) posteriors
  ☆73Updated 5 years ago
• vr308 / Generalised-Gaussian-Processes
  Fully Bayesian Inference in GPs - Gaussian and Generic Likelihoods
  ☆22Updated 2 years ago
• lindermanlab / ssm-jax
  Bayesian learning and inference for state space models (SSMs) using Google Research's JAX as a backend
  ☆61Updated last year