Speaker: Pietro Barbiero (Università della Svizzera Italiana)
Interpretable and neural symbolic AI share a common goal: to enhance the
currently opaque and brittle decision making process of deep learning
methods. To address this issue, I will discuss the design of novel
interpretable deep learning methods endowed with reasoning capabilities. I
will then show how these methods could be applied in diverse real-world
domains, ranging from answering queries on knowledge graphs to
formulating conjectures in universal algebra.
7/11/2023 15:00, Aula Magna, DIAG, Via Ariosto 25, Roma
Pietro Barbiero is Research Assistant at the Università della Svizzera
Italiana (Switzerland). My research activity focuses on interpretable
artificial intelligence, and neural-symbolic models applied to precision
medicine. My current projects are related to interpretable neural reasoning,
explainable AI theory, and AI-assisted conjectures for abstract mathematics.