SATNet, developed by Po-Wei Wang, Priya Donti, Bryan Wilder, and Zico Kolter in 2019, is a differentiable satisfiability solver designed to bridge deep learning and logical reasoning.

Authors

• Person: Not available Organization: arXiv
  Neuro-Symbolic AI: Explainability, Challenges, and Future Trends

Sources

• Neuro-Symbolic AI: Explainability, Challenges, and Future Trends arxiv.org arXiv via serper

Referenced by nodes (2)

• deep learning concept
• logical reasoning concept