Probabilistic morphisms and Bayesian supervised learning
Hông Vân Lê · arXiv (Cornell University) · 2025
In this paper, we develop category theory of Markov kernels to study categorical aspects of Bayesian inversions. As a result, we present a unified model for Bayesian supervised learning, encompassing Bayesian density estimation. We illustrate this model with Gaussian process regressions.