Collaborative Recommendations with Deep Feed-Forward Networks: An Approach to Service Personalization. - Giovanni Luca Cascio Rizzo; Marco De Marco; Pasquale De Rosa; Luigi Laura (IESS, 2020)

Understanding Cryptocoins Trends Correlations. - Pasquale De Rosa; Valerio Schiavoni (DAIS, 2022)

Service Recommendations with Deep Learning: A Study on Neural Collaborative Engines. - Pasquale De Rosa; Michel Deriaz; Marco De Marco; Luigi Laura (Pac. Asia J. Assoc. Inf. Syst., 2022)

Practical Forecasting of Cryptocoins Timeseries using Correlation Patterns. - Pasquale De Rosa; Pascal Felber; Valerio Schiavoni (DEBS, 2023)

Bias Mitigation in Federated Learning for Edge Computing. - Yasmine Djebrouni; Nawel Benarba; Ousmane Touat; Pasquale De Rosa; Sara Bouchenak; Angela Bonifati; Pascal Felber; Vania Marangozova; Valerio Schiavoni (Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2023)

On the Cost of Model-Serving Frameworks: An Experimental Evaluation. - Pasquale De Rosa; Yérom-David Bromberg; Pascal Felber; Djob Mvondo; Valerio Schiavoni (IC2E, 2024)

CryptoAnalytics: Cryptocoins price forecasting with machine learning techniques. - Pasquale De Rosa; Pascal Felber; Valerio Schiavoni (SoftwareX, 2024)

ScamDetect: Towards a Robust, Agnostic Framework to Uncover Threats in Smart Contracts. - Pasquale De Rosa; Pascal Felber; Valerio Schiavoni (DSN-S, 2025)

PhishingHook: Catching Phishing Ethereum Smart Contracts leveraging EVM Opcodes. - Pasquale De Rosa; Simon Queyrut; Yérom-David Bromberg; Pascal Felber; Valerio Schiavoni (DSN-S, 2025)

PhishingHook: Catching Phishing Ethereum Smart Contracts leveraging EVM Opcodes. - Pasquale De Rosa; Simon Queyrut; Yérom-David Bromberg; Pascal Felber; Valerio Schiavoni (Zenodo, 2025)