2 citations · 3 across the 3 of their papers we have counts for
3 papers
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…
Neural DNF-MT: A Neuro-symbolic Approach for Learning Interpretable and Editable Policies
Kexin Gu Baugh, Luke Dickens, Alessandra Russo
Although deep reinforcement learning has been shown to be effective, the model's black-box nature presents barriers to direct policy interpretation. To address this problem, we pro…
Neuro-symbolic Rule Learning in Real-world Classification Tasks
Kexin Gu Baugh, Nuri Cingillioglu, Alessandra Russo
Neuro-symbolic rule learning has attracted lots of attention as it offers better interpretability than pure neural models and scales better than symbolic rule learning. A recent ap…