2 papers
cs.LG2026
Neural Logic Networks for Interpretable Classification
Vincent Perreault, Katsumi Inoue, Richard Labib +1
Traditional neural networks have an impressive classification performance, but what they learn cannot be inspected, verified or extracted. Neural Logic Networks on the other hand h…
cs.LG2025
Disentangling Neural Disjunctive Normal Form Models
Kexin Gu Baugh, Vincent Perreault, Matthew Baugh +3
Neural Disjunctive Normal Form (DNF) based models are powerful and interpretable approaches to neuro-symbolic learning and have shown promising results in classification and reinfo…