2 papers
cs.AI2024
Efficiently Learning Probabilistic Logical Models by Cheaply Ranking Mined Rules
Jonathan Feldstein, Dominic Phillips, Efthymia Tsamoura
Probabilistic logical models are a core component of neurosymbolic AI and are important in their own right for tasks that require high explainability. Unlike neural networks, logic…
cs.AI2023
Principled and Efficient Motif Finding for Structure Learning of Lifted Graphical Models
Jonathan Feldstein, Dominic Phillips, Efthymia Tsamoura
Structure learning is a core problem in AI central to the fields of neuro-symbolic AI and statistical relational learning. It consists in automatically learning a logical theory fr…