Alternatives and similar repositories for hilbert-gp

Users that are interested in hilbert-gp are comparing it to the libraries listed below

• sremes / nonstationary-spectral-kernels
  Implementation for Non-stationary Spectral Kernels (NIPS 2017)
  ☆20Updated 5 years ago
• sremes / nssm-gp
  Non-stationary spectral mixture kernels implemented in GPflow
  ☆28Updated 6 years ago
• wesselb / gpar
  Implementation of the Gaussian Process Autoregressive Regression Model
  ☆67Updated 6 months ago
• gianlucadetommaso / Stein-variational-samplers
  Python and MATLAB code for Stein Variational sampling methods
  ☆25Updated 6 years ago
• yorkerlin / VB-MixEF
  Code for ICML 2019 paper on "Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations"
  ☆18Updated 4 years ago
• thangbui / sparseGP_powerEP
  Unifying sparse approximations for Gaussian process regression and classification, using Power EP
  ☆22Updated 8 years ago
• markusheinonen / adaptivegp
  Fully nonstationary, heteroscedastic GP for Matlab
  ☆15Updated 11 months ago
• secondmind-labs / markovflow
  A Tensorflow based library for Time Series Modelling with Gaussian Processes
  ☆32Updated last year
• rmgarnett / gpml_extensions
  Provides various extensions to the GPML toolbox for Gaussian process inference in MATLAB.
  ☆33Updated 8 years ago
• spdes / chirpgp
  Chirp instantaneous frequency estimation using stochastic differential equation Gaussian processes
  ☆12Updated 8 months ago
• gatsby-sahani / gp-sde
  ☆14Updated 2 years ago
• OxfordML / GPz
  GPz 2.0: Heteroscedastic Gaussian processes for uncertain and incomplete data
  ☆48Updated 4 years ago
• AaltoML / boundary-gp
  Know Your Boundaries: Constraining Gaussian Processes by Variational Harmonic Features
  ☆23Updated 6 years ago
• Tom-Ryder / VIforSDEs
  A variational method for fast, approximate inference for stochastic differential equations.
  ☆44Updated 7 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 7 months ago
• cagatayyildiz / npde
  Nonparametric Differential Equation Modeling
  ☆54Updated last year
• erichanslee / GP_Derivatives
  Scalable Gaussian Process Regression with Derivatives
  ☆38Updated 6 years ago
• ialong / GPt
  Gaussian Processes for Sequential Data
  ☆18Updated 4 years ago
• pmorenoz / ContinualGP
  Continual Gaussian Processes
  ☆32Updated 2 years ago
• RogerFrigola / VGPSSM
  Variational Gaussian Process State-Space Models
  ☆24Updated 9 years ago
• pmorenoz / HetMOGP
  Heterogeneous Multi-output Gaussian Processes
  ☆52Updated 5 years ago
• blei-lab / variational-smc
  Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)
  ☆65Updated 6 years ago
• chengl7 / LonGP
  Gaussian process regression + automatical model selection for logitudinal -omics data
  ☆21Updated 4 years ago
• aterenin / SparseGPAX
  An ultra-lightweight JAX implementation of sparse Gaussian processes via pathwise sampling.
  ☆22Updated 4 years ago
• amzn / orthogonal-additive-gaussian-processes
  Light-weighted code for Orthogonal Additive Gaussian Processes
  ☆43Updated 11 months ago
• trappmartin / DeepStructuredMixtures
  Code for Deep Structured Mixtures of Gaussian Processes (DSMGPs)
  ☆11Updated 3 years ago
• j-wilson / GPflowSampling
  Code for efficiently sampling functions from GP(flow) posteriors
  ☆72Updated 4 years ago
• stefanosele / GPfY
  Gaussian processes with spherical harmonic features in JAX
  ☆15Updated last year
• PredictiveIntelligenceLab / GP-NODEs
  ☆29Updated 2 years ago
• kpchamp / MultiscaleDiscovery
  ☆28Updated 7 years ago