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Distilling data into code

delete2024-02-19
delete0
PRE
AI
J
Joseph Bakarji *
DOI：10.1038/s43588-024-00598-4delete
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Abstract

Abstract

En 中文
One of the greatest limitations of deep neural networks is the difficulty of interpreting what they learn from the data. Deep distilling addresses this problem by extracting human-comprehensible and executable code from observations.

Journal

Nature Computational Science cover
Nature Computational Science
IF:
18.3
Papers:
3.1K
Citations:
4.0K

Organization

A
American University of Beirut
Scholars:
8.3K
Papers: 6.0K
Citations: 1.1W
Cited Papers

Cited Papers

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