Seminar Details
2026-01-23 (11:00) : Neuro-symbolic Deep Learning with Requirements
At Shannon, Maxwell a.105
Organized by Computer Science and Engineering
Speaker :
Eleonora Giunchiglia (Assistant Professor in Machine Learning and AI at Imperial College London | PI of DUCK Lab)
Abstract :
For their outstanding ability of finding hidden patterns in data, deep learning models have been extensively applied in many different domains. However, recent works have shown that, if a set of requirements expressing inherent knowledge about the problem at hand is given, then neural networks often fail to comply with them. This represents a major drawback for deep learning models, as requirements compliance is normally considered a necessary condition for standard software deployment. We present a neuro-symbolic framework able to make any neural network compliant by design to a given set of requirements over the output space expressed in full propositional logic. This framework integrates the requirements into the output layer of the neural network.