Search Results for author:
Found 2 papers, 1 papers with code
Scalable Neural-Probabilistic Answer Set Programming
The goal of combining the robustness of neural networks and the expressiveness of symbolic methods has rekindled the interest in Neuro-Symbolic AI.
SLASH: Embracing Probabilistic Circuits into Neural Answer Set Programming
The probability estimates resulting from NPPs act as the binding element between the logical program and raw input data, thereby allowing SLASH to answer task-dependent logical queries.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
