SpiderNet: Fully Connected Residual Network for Fraud Detection

Author:

Afanasiev S. V.,Smirnova A. A.,Kotereva D. M.

Publisher

Pleiades Publishing Ltd

Reference22 articles.

1. R. J. Bolton and D. J. Hand, “Statistical fraud detection: A review,” Stat. Sci. 17 (3), 235–255 (1999). https://doi.org/10.1214/ss/1042727940

2. A. Krizhevsky, I. Sutskever, and G. E. Hinton, “ImageNet classification with deep convolutional neural networks” (2012). http://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks.pdf

3. K. He, X. Zhang, S. Ren, and J. Sun, “Deep residual learning for image recognition,” Microsoft Research (2015). https://arxiv.org/pdf/1512.03385v1.pdf

4. A. van den Oord, S. Dieleman, H. Zen, K. Simonyan, O. Vinyals, A. Graves, N. Kalchbrenner, A. Senior, and K. Kavukcuoglu, “Wavenet: A generative model for raw audio” (2016). arXiv:1609.03499

5. R. Paulus, C. Xiong, and R. Socher, “A deep reinforced model for abstractive summarization” (2017). arXiv:1705.04304

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