NLARE, a natural language processing tool for automatic requirements evaluation. - Carlos Huertas; Reyes Juárez-Ramírez (CUBE, 2012)

Automated Generation of User-Interface Prototypes Based on Controlled Natural Language Description. - Reyes Juárez-Ramírez; Carlos Huertas; Sergio Inzunza (COMPSAC Workshops, 2014)

Filter feature selection performance comparison in high-dimensional data: A theoretical and empirical analysis of most popular algorithms. - Carlos Huertas; Reyes Juárez-Ramírez (FUSION, 2014)

Heat Map Based Feature Selection: A Case Study for Ovarian Cancer. - Carlos Huertas; Reyes Juárez-Ramírez (EvoApplications, 2015)

Heat Map Based Feature Ranker: In depth comparison with popular methods. - Carlos Huertas; Reyes Juárez-Ramírez; Christian Raymond (Intell. Data Anal., 2018)

Efficient and Effective Uncertainty Quantification in Gradient Boosting via Cyclical Gradient MCMC. - Tian Tan 018; Carlos Huertas; Qi Zhao (SafeAI@AAAI, 2023)

On The Irrelevance of Machine Learning Algorithms and the Importance of Relativity. - Carlos Huertas; Qi Zhao (ICME Workshops, 2023)

Gradient Boosting Trees and Large Language Models for Tabular Data Few-Shot Learning. - Carlos Huertas (FedCSIS (Communication Papers), 2024)