Distilling data into code

doi:10.1038/s43588-024-00598-4

2024-02-19

PRE

Joseph Bakarji *

DOI：10.1038/s43588-024-00598-4

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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.

期刊

Nature Computational Science

IF:

18.3

论文数:

3.1K

被引数:

4.0K

机构

American University of Beirut

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被引数: 1.1W

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