Simplifying Fitness Landscapes Using Dilation Functions Evolved With Genetic Programming. - Daniele M. Papetti; Andrea Tangherloni; Davide Farinati; Paolo Cazzaniga; Leonardo Vanneschi (IEEE Comput. Intell. Mag., 2023)

A study of dynamic populations in geometric semantic genetic programming. - Davide Farinati; Illya Bakurov; Leonardo Vanneschi (Inf. Sci., 2023)

GM4OS: An Evolutionary Oversampling Approach for Imbalanced Binary Classification Tasks. - Davide Farinati; Leonardo Vanneschi (EvoApplications@EvoStar, 2024)

A survey on dynamic populations in bio-inspired algorithms. - Davide Farinati; Leonardo Vanneschi (Genet. Program. Evolvable Mach., 2024)

Exploring the Impact of Data Scale on Mutation Step Size in SLIM-GSGP. - Davide Farinati; Gloria Pietropolli; Leonardo Vanneschi (EuroGP, 2025)

Introducing Crossover in SLIM-GSGP. - Gloria Pietropolli; Davide Farinati; Luca Manzoni; Mauro Castelli; Sara Silva; Leonardo Vanneschi (EuroGP, 2025)

Exploring the Integration of Cellular Structures in Genetic Programming-Based Methods. - Luigi Rovito; Lorenzo Bonin; Davide Farinati; Leonardo Vanneschi; Luca Manzoni; Andrea De Lorenzo; Gloria Pietropolli (EuroGP, 2025)

Slim_gsgp: A Python Library for Non-Bloating GSGP. - Liah Rosenfeld; Davide Farinati; Diogo Rasteiro; Gloria Pietropolli; Karina Brotto Rebuli; Sara Silva; Leonardo Vanneschi (GECCO, 2025)

An Empirical Study of GM4OS for Imbalanced Binary Classification. - Davide Farinati; Leonardo Vanneschi (SN Comput. Sci., 2025)