markovflow

API reference documentation for the Markovflow package.

Markovflow includes ready-to-use GP models for classification and regression.

If you want to create your own model, you must implement either the MarkovFlowModel or the MarkovFlowSparseModel base class.

Subpackages

• markovflow.kernels
  • markovflow.kernels.constant
  • markovflow.kernels.kernel
  • markovflow.kernels.latent_exp_generated
  • markovflow.kernels.matern
  • markovflow.kernels.periodic
  • markovflow.kernels.piecewise_stationary
  • markovflow.kernels.sde_kernel
• markovflow.likelihoods
  • markovflow.likelihoods.likelihoods
  • markovflow.likelihoods.multivariate_gaussian
  • markovflow.likelihoods.mutlistage_likelihood
• markovflow.models
  • markovflow.models.gaussian_process_regression
  • markovflow.models.iwvi
  • markovflow.models.models
  • markovflow.models.pep
  • markovflow.models.sparse_pep
  • markovflow.models.sparse_variational
  • markovflow.models.sparse_variational_cvi
  • markovflow.models.spatio_temporal_variational
  • markovflow.models.variational
  • markovflow.models.variational_cvi
• markovflow.sde
  • markovflow.sde.drift
  • markovflow.sde.sde_utils

Submodules

• markovflow.base
• markovflow.block_tri_diag
• markovflow.conditionals
• markovflow.emission_model
• markovflow.gauss_markov
• markovflow.kalman_filter
• markovflow.mean_function
• markovflow.posterior
• markovflow.ssm_gaussian_transformations
• markovflow.ssm_natgrad
• markovflow.state_space_model
• markovflow.utils