Improving Performance in Neural Networks by Dendrites-Activated Connections. - Carlo Metta; Marco Fantozzi; Andrea Papini; Gianluca Amato; Matteo Bergamaschi; Silvia Giulia Galfrè; Alessandro Marchetti; Michelangelo Vegliò; Maurizio Parton; Francesco Morandin (CoRR, 2023)

How Much Do DNA and Protein Deep Embeddings Preserve Biological Information? - Matteo Tolloso; Silvia Giulia Galfrè; Arianna Pavone; Marco Podda; Alina Sîrbu; Corrado Priami (CMSB, 2024)

A Systematization of the Wagner Framework: Graph Theory Conjectures and Reinforcement Learning. - Flora Angileri; Giulia Lombardi; Andrea Fois; Renato Faraone; Carlo Metta; Michele Salvi; Luigi Amedeo Bianchi; Marco Fantozzi; Silvia Giulia Galfrè; Daniele Pavesi; Maurizio Parton; Francesco Morandin (DS (1), 2024)

SwitchPath: Enhancing Exploration in Neural Networks Learning Dynamics. - Antonio Di Cecco; Andrea Papini; Carlo Metta; Marco Fantozzi; Silvia Giulia Galfrè; Francesco Morandin; Maurizio Parton (DS (1), 2024)

Increasing biases can be more efficient than increasing weights. - Carlo Metta; Marco Fantozzi; Andrea Papini; Gianluca Amato; Matteo Bergamaschi; Silvia Giulia Galfrè; Alessandro Marchetti; Michelangelo Vegliò; Maurizio Parton; Francesco Morandin (WACV, 2024)

Achieving Predictive Precision: Leveraging LSTM and Pseudo Labeling for Volvo's Discovery Challenge at ECML-PKDD 2024. - Carlo Metta; Marco Gregnanin; Andrea Papini; Silvia Giulia Galfrè; Andrea Fois; Francesco Morandin; Marco Fantozzi; Maurizio Parton (CoRR, 2024)

Increasing biases can be more efficient than increasing weights. - Carlo Metta; Marco Fantozzi; Andrea Papini; Gianluca Amato; Matteo Bergamaschi; Andrea Fois; Silvia Giulia Galfrè; Alessandro Marchetti; Michelangelo Vegliò; Maurizio Parton; Francesco Morandin (Adv. Data Anal. Classif., 2025)