Learning a Formula of Interpretability to Learn Interpretable Formulas. - Marco Virgolin; Andrea De Lorenzo; Eric Medvet; Francesca Randone (PPSN (2), 2020)

Model learning with personalized interpretability estimation (ML-PIE). - Marco Virgolin; Andrea De Lorenzo; Francesca Randone; Eric Medvet; Mattias Wahde (GECCO Companion, 2021)

Refining Mean-field Approximations by Dynamic State Truncation. - Francesca Randone; Luca Bortolussi; Mirco Tribastone (Proc. ACM Meas. Anal. Comput. Syst., 2021)

Jump Longer to Jump Less: Improving Dynamic Boundary Projection with h-Scaling. - Francesca Randone; Luca Bortolussi; Mirco Tribastone (QEST, 2022)

Symbolic Quantitative Information Flow for Probabilistic Programs. - Philipp Schröer; Francesca Randone; Raúl Pardo; Andrzej Wasowski (Principles of Verification (1), 2024)

Towards a Probabilistic Programming Approach to Analyse Collective Adaptive Systems. - Francesca Randone; Romina Doz; Francesca Cairoli; Luca Bortolussi (ISoLA (1), 2024)

Inference of Probabilistic Programs with Moment-Matching Gaussian Mixtures. - Francesca Randone; Luca Bortolussi; Emilio Incerto; Mirco Tribastone (Proc. ACM Program. Lang., 2024)

Evolutionary Synthesis of Probabilistic Programs. - Romina Doz; Francesca Randone; Eric Medvet; Luca Bortolussi (GECCO, 2025)

Foundations for Deductive Verification of Continuous Probabilistic Programs: From Lebesgue to Riemann and Back. - Kevin Batz; Joost-Pieter Katoen; Francesca Randone; Tobias Winkler 001 (Proc. ACM Program. Lang., 2025)