2 citations · 2 across the 3 of their papers we have counts for
3 papers
LTNtorch: PyTorch Implementation of Logic Tensor Networks
Tommaso Carraro, Luciano Serafini, Fabio Aiolli
Logic Tensor Networks (LTN) is a Neuro-Symbolic framework that effectively incorporates deep learning and logical reasoning. In particular, LTN allows defining a logical knowledge…
Towards Counting Markov Equivalence Classes with Logical Constraints
Davide Bizzaro, Luciano Serafini, Sagar Malhotra
We initiate the study of counting Markov Equivalence Classes (MEC) under logical constraints. MECs are equivalence classes of Directed Acyclic Graphs (DAGs) that encode the same co…
Simple and Effective Transfer Learning for Neuro-Symbolic Integration
Alessandro Daniele, Tommaso Campari, Sagar Malhotra +1
Deep Learning (DL) techniques have achieved remarkable successes in recent years. However, their ability to generalize and execute reasoning tasks remains a challenge. A potential…