Ricardo García-Ródenas

A comparative study of machine learning, deep neural networks and random utility maximization models for travel mode choice modelling
IoT based monitoring of air quality and traffic using regression analysis
A Python package for performing penalized maximum likelihood estimation of conditional logit models using Kernel Logistic Regression
Revisiting kernel logistic regression under the random utility models perspective. An interpretable machine-learning approach
A comparison of general-purpose optimization algorithms for finding optimal approximate experimental designs
Discrete choice modeling using Kernel Logistic Regression