Author:
Jiang Wenlong,Yin Pei,Zhu Wangwei
Publisher
Springer Nature Switzerland
Reference15 articles.
1. Chandradeva, L.S., Amarasinghe, T.M., de Silvam, M., et al.: Monetary transaction fraud detection system based on machine learning strategies. In: Proceedings of the 4th International Congress on Information and Communication Technology, pp. 385–396 (2020)
2. Sürücü, O., et al.: A survey on ethereum smart contract vulnerability detection using machine learning. In: Proceedings SPIE 12117, Disruptive Technologies in Information Sciences VI, 121170C (2022)
3. Kurshan, E., Shen, H., Yu, H.: Financial crime & fraud detection using graph computing: application considerations & outlook. In: Proceedings of the 2020 Second International Conference on Transdisciplinary AI (TransAI), pp. 542–549 (2020)
4. Somepalli, G., Goldblum, M., Schwarzschild, A., Bruss, C.B., Goldstein, T.: SAINT: improved neural networks for tabular data via row attention and contrastive pre-training (2021). arXiv:2106.01342v1 [cs.LG]
5. Dazeley, R.P.: To the knowledge frontier and beyond: a hybrid system for incremental contextual-learning and prudence analysis. PhD thesis (2006)