trilearn
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trilearn

  • Subpackages
  • Distributions
  • Auxiliary functions
  • Graph predictive classification
  • P. Green & A. Thomas MH-sampler
  • Particle Gibbs
  • Stochastic set process
  • SMC
trilearn
  • Overview: module code

All modules for which code is available

  • trilearn.auxiliary_functions
  • trilearn.distributions.dirichlet
  • trilearn.distributions.discrete_dec_log_linear
  • trilearn.distributions.g_intra_class
  • trilearn.distributions.g_inv_wishart
  • trilearn.distributions.gaussian_graphical_model
  • trilearn.distributions.matrix_multivariate_normal
  • trilearn.distributions.multivariate_students_t
  • trilearn.distributions.sequential_junction_tree_distributions
  • trilearn.distributions.wishart
  • trilearn.graph.decomposable
  • trilearn.graph.empirical_graph_distribution
  • trilearn.graph.graph
  • trilearn.graph.greenthomas
  • trilearn.graph.junction_tree
  • trilearn.graph.junction_tree_collapser
  • trilearn.graph.junction_tree_expander
  • trilearn.graph.subtree_sampler
  • trilearn.graph.trajectory
  • trilearn.mh_greenthomas
  • trilearn.pgibbs
  • trilearn.set_process
  • trilearn.smc

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