Machine Learning, Agile, Markov Chains, Bayesian Statistics, TensorFlow.
step_size_update_fn=tfp.mcmc.make_simple_step_size_update_policy(), seed=1398) # Run the chain (with burn-in). samples, kernel_results = tfp.mcmc.sample_chain( num_results=int(1e5), #num_burnin_steps=int(1e1), current_state=[10.0,2.0,0.2], kernel=hmc) # Initialize all constructed variables. init_op