國立虎尾科技大學 |

Neurosymbolic Learning and Reasoning for Trustworthy AI.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	Neurosymbolic Learning and Reasoning for Trustworthy AI./
Author:	Zeng, Zhe.
Description:	1 online resource (219 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 85-12, Section: B.
Contained By:	Dissertations Abstracts International85-12B.
Subject:	Computer science. -
Online resource:	click for full text (PQDT)
ISBN:	9798382838519

Neurosymbolic Learning and Reasoning for Trustworthy AI.
Zeng, Zhe.

Neurosymbolic Learning and Reasoning for Trustworthy AI. - 1 online resource (219 pages)

Source: Dissertations Abstracts International, Volume: 85-12, Section: B.

Thesis (Ph.D.)--University of California, Los Angeles, 2024.

Includes bibliographical references

Along with the ubiquitous applications of Artificial Intelligence (AI), the quest for developing trustworthy AI models intensifies. Deep neural networks, while powerful in learning, fall short in reasoning with domain knowledge and offering robustness guarantees. Neurosymbolic AI bridges this gap by melding the learning capabilities of neural networks and reasoning techniques from symbolic AI, thus building models that behave as intended. This dissertation demonstrates my work that addresses the two fundamental challenges in neurosymbolic AI: 1) enabling differentiable learning of deep neural networks under symbolic constraints and 2) performing scalable and reliable probabilistic reasoning over expressive symbolic constraints. It presents how these neurosymbolic approaches achieve trustworthiness through explainability, uncertainty quantification, and domain-knowledge incorporation. These contributions enable broader applications of neurosymbolic AI in various domains including scientific discoveries.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024

Mode of access: World Wide Web

ISBN: 9798382838519Subjects--Topical Terms:

573171
Computer science.
Subjects--Index Terms:

Machine learningIndex Terms--Genre/Form:

554714
Electronic books.

Neurosymbolic Learning and Reasoning for Trustworthy AI.
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