Multi-Objective reward generalization: Improving performance of Deep Reinforcement Learning for selected applications in stock and cryptocurrency trading. - Federico Cornalba; Constantin Disselkamp; Davide Scassola; Christopher Helf (CoRR, 2022)

Model Abstraction and Conditional Sampling with Score-Based Diffusion Models. - Luca Bortolussi; Francesca Cairoli; Francesco Giacomarra; Davide Scassola (QEST, 2023)

Conditioning Score-Based Generative Models by Neuro-Symbolic Constraints. - Davide Scassola; Sebastiano Saccani; Ginevra Carbone; Luca Bortolussi (CoRR, 2023)

Multi-objective reward generalization: improving performance of Deep Reinforcement Learning for applications in single-asset trading. - Federico Cornalba; Constantin Disselkamp; Davide Scassola; Christopher Helf (Neural Comput. Appl., 2024)

Zero-Shot Conditioning of Score-Based Diffusion Models by Neuro-Symbolic Constraints. - Davide Scassola; Sebastiano Saccani; Ginevra Carbone; Luca Bortolussi (AAAI, 2025)

Graph Conditional Flow Matching for Relational Data Generation. - Davide Scassola; Sebastiano Saccani; Luca Bortolussi (CoRR, 2025)