Injective Domain Knowledge in Neural Networks for Transprecision Computing. - Andrea Borghesi; Federico Baldo; Michele Lombardi 001; Michela Milano (LOD (1), 2020)

Lagrangian Duality for Constrained Deep Learning. - Ferdinando Fioretto; Pascal Van Hentenryck; Terrence W. K. Mak; Cuong Tran 007; Federico Baldo; Michele Lombardi 001 (ECML/PKDD (5), 2020)

An Analysis of Regularized Approaches for Constrained Machine Learning. - Michele Lombardi 001; Federico Baldo; Andrea Borghesi; Michela Milano (TAILOR, 2020)

A Lagrangian Dual Framework for Deep Neural Networks with Constraints. - Ferdinando Fioretto; Terrence W. K. Mak; Federico Baldo; Michele Lombardi 001; Pascal Van Hentenryck (CoRR, 2020)

Improving Deep Learning Models via Constraint-Based Domain Knowledge: a Brief Survey. - Andrea Borghesi; Federico Baldo; Michela Milano (CoRR, 2020)

Deep Learning for Virus-Spreading Forecasting: a Brief Survey. - Federico Baldo; Lorenzo Dall'Olio; Mattia Ceccarelli; Riccardo Scheda; Michele Lombardi 001; Andrea Borghesi; Stefano Diciotti; Michela Milano (CoRR, 2021)

Informed Deep Learning for Epidemics Forecasting. - Federico Baldo; Michele Iannello; Michele Lombardi 001; Michela Milano (PAIS@ECAI, 2022)

An Analysis of Universal Differential Equations for Data-Driven Discovery of Ordinary Differential Equations. - Mattia Silvestri; Federico Baldo; Eleonora Misino; Michele Lombardi 001 (ICCS (4), 2023)

Discovering maximally consistent distribution of causal tournaments with Large Language Models. - Federico Baldo; Simon Ferreira; Charles K. Assaad (CoRR, 2024)

Informed machine learning for epidemics: from data analysis to time-series forecasting. - Federico Baldo (2024)

Enhancing Cell Counting through MLOps: A Structured Approach for Automated Cell Analysis. - Matteo Testi; Luca Clissa; Matteo Ballabio; Salvatore Ricciardi; Federico Baldo; Emanuele Frontoni; Sara Moccia; Gennaro Vessio (CoRR, 2025)