Kernel embedding of maps for sequential Bayesian inference: The variational mapping particle filter. - Manuel Pulido; Peter Jan van Leeuwen (CoRR, 2018)

Kernel Embedded Nonlinear Observational Mappings in the Variational Mapping Particle Filter. - Manuel Pulido; Peter Jan van Leeuwen; Derek J. Posselt (ICCS (4), 2019)

Sequential Monte Carlo with kernel embedded mappings: The mapping particle filter. - Manuel Pulido; Peter Jan van Leeuwen (J. Comput. Phys., 2019)

A new Framework for Causal Discovery. - Peter Jan van Leeuwen; Michael DeCaria; Nachiketa Chakaborty; Manuel Pulido (CoRR, 2020)

Evaluation of Machine Learning Techniques for Forecast Uncertainty Quantification. - Maximiliano A. Sacco; Juan J. Ruiz; Manuel Pulido; Pierre Tandeo (CoRR, 2021)

Model Error Estimation Using the Expectation Maximization Algorithm and a Particle Flow Filter. - María Magdalena Lucini; Peter Jan van Leeuwen; Manuel Pulido (SIAM/ASA J. Uncertain. Quantification, 2021)

Online machine-learning forecast uncertainty estimation for sequential data assimilation. - Maximiliano A. Sacco; Manuel Pulido; Juan J. Ruiz; Pierre Tandeo (CoRR, 2023)

The impact of fine tuning in LLaMA on hallucinations for named entity extraction in legal documentation. - Francisco Vargas 005; Alejandro González Coene; Gaston Escalante; Exequiel Lobón; Manuel Pulido (CoRR, 2025)