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.

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

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).

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

Generating Multi-State Survival Data