tf.contrib.bayesflow

 

upper level

 

Modules

 

csiszar_divergence:

Csiszar f-Divergence and helpers.

custom_grad:

Functions for specifying custom gradients.

halton_sequence:

Support for low discrepancy Halton sequences.

hmc:

Hamiltonian Monte Carlo, a gradient-based MCMC algorithm.

layers:

Probabilistic neural layers.

metropolis_hastings:

Functions to create a Markov Chain Monte Carlo Metropolis step.

monte_carlo:

Monte Carlo integration and helpers.

optimizers:

Probabilistic optimizer modules.

 

Classes

 

None

 

Functions

 

None