arXiv Open Access 2022

Neurosymbolic Programming for Science

Jennifer J. Sun Megan Tjandrasuwita Atharva Sehgal Armando Solar-Lezama Swarat Chaudhuri +2 lainnya

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Abstrak

Neurosymbolic Programming (NP) techniques have the potential to accelerate scientific discovery. These models combine neural and symbolic components to learn complex patterns and representations from data, using high-level concepts or known constraints. NP techniques can interface with symbolic domain knowledge from scientists, such as prior knowledge and experimental context, to produce interpretable outputs. We identify opportunities and challenges between current NP models and scientific workflows, with real-world examples from behavior analysis in science: to enable the use of NP broadly for workflows across the natural and social sciences.

Topik & Kata Kunci

cs.AI

Penulis (7)

Jennifer J. Sun

Megan Tjandrasuwita

Atharva Sehgal

Armando Solar-Lezama

Swarat Chaudhuri

Yisong Yue

Omar Costilla-Reyes

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APA MLA BibTeX

Sun, J.J., Tjandrasuwita, M., Sehgal, A., Solar-Lezama, A., Chaudhuri, S., Yue, Y. et al. (2022). Neurosymbolic Programming for Science. https://arxiv.org/abs/2210.05050

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Informasi Jurnal

Tahun Terbit: 2022
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓