In this notebook I explore the Bayesian Decision Theory Workflow described in the amazing blog post A Bayesian Decision Theory Workflow by Daniel Saunders. It is a great resource to understand how to use Bayesian methods for optimization problems. In the original post, Daniel explains the theory and key concepts using PyMC and its computational backend PyTensor. He does a remarkable job presenting powerful PyTensor features to manipulate and operate with symbolic computational graphs. I can only recommend you to read it!
Dr. Juan Camilo Orduz · Jan 25, 2026
A Bayesian Decision Theory Workflow: Port to NumPyro
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In this notebook I explore the Bayesian Decision Theory Workflow described in the amazing blog post A Bayesian Decision Theory Workflow by Daniel Saunders . It is a great resource to understand how to use Bayesian methods for optimization problems. In the original post, Daniel explains the theory and key concepts using PyMC and its computational backend PyTensor . He does a remarkable job…
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