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EGAIN: Enhanced Generative Adversarial Networks for Imputing Missing Values

Abolfazl Saghafi Soodeh Moallemian Miray Budak Rutvik Deshpande

Computers, Materials & Continua2026，Vol.88Issue(8)：P.2241-2255,15.

Computers, Materials & Continua2026，Vol.88Issue(8)：P.2241-2255,15.DOI:10.32604/cmc.2026.082996

EGAIN: Enhanced Generative Adversarial Networks for Imputing Missing Values

Abolfazl Saghafi ¹Soodeh Moallemian ²Miray Budak ²Rutvik Deshpande²

作者信息

1. Department of Mathematics,Saint Joseph’s University,Philadelphia,PA,USA
2. Center for Molecular&Behavioral Neuroscience,Rutgers University–Newark,Newark,NJ,USA
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摘要

关键词

Missing value imputation/generative adversarial network/tabular data imputation/missing completely at random/convolutional architectures/training stability

分类

信息技术与安全科学

引用本文复制引用

Abolfazl Saghafi,Soodeh Moallemian,Miray Budak,Rutvik Deshpande..EGAIN: Enhanced Generative Adversarial Networks for Imputing Missing Values[J].Computers, Materials & Continua,2026,88(8):P.2241-2255,15.

Computers, Materials & Continua

ISSN：1546-2218

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