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HeteroGCL: A Heterogeneous Graph Contrastive Learning Framework for Scalable and Sustainable Cryptocurrency AML.

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Title: HeteroGCL: A Heterogeneous Graph Contrastive Learning Framework for Scalable and Sustainable Cryptocurrency AML.
Authors: Chen, Jiaying1, Liu, Jingyi2, Liang, Yiwen1,3, yl2947@cornell.edu, Zhou, Mengjie1,3
Source: Applied Sciences (2076-3417); Mar2026, Vol. 16 Issue 6, p2860, 27p
Database: Applied Science & Technology Source
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  Data: HeteroGCL: A Heterogeneous Graph Contrastive Learning Framework for Scalable and Sustainable Cryptocurrency AML.
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        Value: 10.3390/app16062860
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      – Code: eng
        Text: English
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      – TitleFull: HeteroGCL: A Heterogeneous Graph Contrastive Learning Framework for Scalable and Sustainable Cryptocurrency AML.
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            NameFull: Chen, Jiaying
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            NameFull: Liu, Jingyi
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              Text: Mar2026
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