PiShield: A NeSy Framework for Learning with Requirements
Mihaela Cătălina Stoian Alex Tatomir Thomas Lukasiewicz Eleonora Giunchiglia
Deep learning models have shown their strengths in various application
domains, however, they often struggle to meet safety requirements for their
outputs. In this paper, we introduce PiShield, the first framework ever
allowing for the integration of the requirements into the neural networks'
topology. PiShield guarantees compliance with these requirements, regardless of
input. Additionally, it allows for integrating requirements both at inference
and/or training time, depending on the practitioners' needs. Given the
widespread application of deep learning, there is a growing need for frameworks
allowing for the integration of the requirements across various domains. Here,
we explore three application scenarios: functional genomics, autonomous
driving, and tabular data generation.