Attentive Feature Fusion for Credit Default Prediction

Author:

Liu Ximing1,Li Yayong2,Jiang Cuiqing1,Wang Zhao1,Zhao Fuqing3,Wang Jianfei1

Affiliation:

1. Hefei University of Technology,Hefei,China

2. University of Technology Sydney,Sydney,Australia

3. Lanzhou University of Technology,Lanzhou,China

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Publisher

IEEE

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Predicting financial distress using multimodal data: An attentive and regularized deep learning method;Information Processing & Management;2024-07

2. A Lightweight Neural Network with Transformer to Predict Credit Default;2024 IEEE Conference on Artificial Intelligence (CAI);2024-06-25

3. Credit Default Prediction on Time-Series Behavioral Data Using Ensemble Models;2023 International Joint Conference on Neural Networks (IJCNN);2023-06-18

4. Default Prediction on Commercial Credit Big Data Using Graph-based Variable Clustering;2023 IEEE 17th International Conference on Semantic Computing (ICSC);2023-02

5. Hybrid model for detection of frauds in credit cards*;2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N);2022-12-16

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