Mining Context-Aware Preferences on Relational and Sensor Data. - Davide Beretta; Elisa Quintarelli; Emanuele Rabosio (DEXA Workshops, 2011)

Functional Principal Component Analysis as a Versatile Technique to Understand and Predict the Electric Consumption Patterns. - Davide Beretta; Samuele Grillo; Davide Pigoli; Enea Bionda; Claudio Bossi; Carlo Tornelli (CoRR, 2019)

Texture-based classification of lung disease patterns in chronic hypersensitivity pneumonitis and comparison to clinical outcomes. - Francesca Pennati; Lorenzo Aliboni; Alessio Antoniazza; Davide Beretta; Olívia Meira Dias; Bruno Guedes Baldi; Marcio Sawamura; Rodrigo Caruso Chate; Carlos Roberto Ribeiro De Carvalho; André Luis Pereira de Albuquerque; Andrea Aliverti (EMBC, 2021)

Recent Neural-Symbolic Approaches to ILP Based on Templates. - Davide Beretta; Stefania Monica; Federico Bergenti (EXTRAAMAS@AAMAS, 2022)

A Comparative Study of Three Neural-Symbolic Approaches to Inductive Logic Programming. - Davide Beretta; Stefania Monica; Federico Bergenti (LPNMR, 2022)

Preliminary Results on a State-Driven Method for Rule Construction in Neural-Symbolic Reinforcement Learning. - Davide Beretta; Stefania Monica; Federico Bergenti (NeSy, 2023)

Capturing a Recursive Pattern in Neural-Symbolic Reinforcement Learning. - Davide Beretta; Stefania Monica; Federico Bergenti (WOA, 2023)

State and Action Factorization in Power Grids. - Gianvito Losapio; Davide Beretta; Marco Mussi; Alberto Maria Metelli; Marcello Restelli (CoRR, 2024)