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Efficient multimodal learning for corporate credit risk prediction with an extended deep belief network.

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Title: Efficient multimodal learning for corporate credit risk prediction with an extended deep belief network.
Authors: Lu, Sichong1 (AUTHOR) lusc413@foxmail.com, Zhang, Xiaoming2 (AUTHOR) zhxmdy@163.com, Su, Yi1 (AUTHOR) suyi@hrbeu.edu.cn, Liu, Xiaojun3 (AUTHOR) lxj02041820@163.com, Yu, Lean1,4 (AUTHOR) yulean@amss.ac.cn
Source: Annals of Operations Research. Jun2026, Vol. 361 Issue 1, p309-346. 38p.
Database: Business Source Ultimate
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  Data: Efficient multimodal learning for corporate credit risk prediction with an extended deep belief network.
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  Data: <searchLink fieldCode="JN" term="%22Annals+of+Operations+Research%22">Annals of Operations Research</searchLink>. Jun2026, Vol. 361 Issue 1, p309-346. 38p.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=bsu&AN=194091815
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      – Type: doi
        Value: 10.1007/s10479-025-06612-w
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      – Code: eng
        Text: English
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        PageCount: 38
        StartPage: 309
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      – TitleFull: Efficient multimodal learning for corporate credit risk prediction with an extended deep belief network.
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            NameFull: Lu, Sichong
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            NameFull: Zhang, Xiaoming
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            NameFull: Su, Yi
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            NameFull: Liu, Xiaojun
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            – D: 01
              M: 06
              Text: Jun2026
              Type: published
              Y: 2026
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              Value: 361
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