Neuro-symbolic AI research is categorized into several domains: mathematics and symbolic regression (e.g., Majumdar et al., 2023; Petersen et al., 2019), logic and knowledge processing including concept/rule learning (e.g., Aspis et al., 2022) and logical reasoning (e.g., Cunnington et al., 2023), and applications such as visual question answering (e.g., Mao et al., 2019), medical (e.g., Jain et al., 2023), communication (e.g., Thomas and Saad, 2023), programming (e.g., Hu et al., 2022a), recommendation systems (e.g., Carraro, 2023), and security (e.g., Wang et al., 2018).

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 (5)

• Neuro-symbolic artificial intelligence concept
• logical reasoning concept
• logic concept
• Deep Symbolic Regression concept
• Visual Question Answering concept