Author

Weiyan Zhu

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Open access Jul 2026

Explainable Deep Tabular Learning for Credit Risk Assessment: An Information-Theoretic Cross-Attentional Transformer Approach

This study develops an explainable machine learning framework for modeling loan approval decisions on heterogeneous tabular data, centered on a Cross-Attentional Tabular Transformer that applies bidirectional cross-attention between numerical and categorical feature groups.

Bowen Dong, Xinyu Zhang, Ziwei Hong et al. · Entropy · 0 citations