Automatic probabilistic programming for scientific machine learning and dynamical models

We present a user-friendly open-source Matlab package for stochastic data analysis that enables to perform a standard analysis of given turbulent data and extracts the stochastic equations describing the scale-dependent cascade process in turbulent flows through Fokker-Planck equations and concepts of non-equilibrium stochastic thermodynamics.

Bayesian inference for Discrete state-space Partially Observed Markov Processes in Julia. See the docs:

Apuntes de Ingeniería Civil Matemática, con electivos en Computación y Aprendizaje.

An Open Source Tool for Analyzing Discrete Markov Chains.

End-to-End Python implementation of Azcue et al.'s (2025) stochastic optimal control framework for social protection policy design. Solves PDMP-based Hamilton-Jacobi-Bellman equations using analytical closed-form solutions and Monte Carlo simulation to minimize government intervention costs (through the use of cash transfers and microinsurance).

Generating Multi-State Survival Data

Algunos archivos .tex de las tareas correspondientes al curso de Procesos de Markov de la maestría en proba y estadística del CIMAT

Code used in "Minimizing Information Leakage of Abrupt Changes in Stochastic Systems" , by Alessio Russo, alessior@kth.se .