Science Score: 36.0%

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  • Host: GitHub
  • Owner: antotu
  • Language: Python
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  • Size: 33.7 MB
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Created almost 2 years ago · Last pushed almost 2 years ago
Metadata Files
Readme Citation

README.md

Evaluating the computational advantages of the Variational Quantum Circuit model in Financial Fraud Detection

Authors: Antonio Tudisco, Deborah Volpe, Giacomo Ranieri', Gianbiagio Curato', Davide Ricossa', Mariagrazia Graziano*, Davide Corbelletto'

*VLSI Lab, Politecnico di Torino, Torino, Italy

'Intesa Sanpaolo, Torino, Italy

Journal: IEEE Access

doi: (10.1109/ACCESS.2024.3432312)

url: https://ieeexplore.ieee.org/abstract/document/10606260

Scripts employed for training, test and validation and pretrained models presented in the article are available in this repository.

If you have any questions, feel free to create a discussion or an issue on GitHub.

Acknowledgements

The authors would like to thank the Intesa Sanpaolo Quantum Competence Center for granting access to IBM Quantum Runtime Services (Pay-as-you-go plan) and HPC@POLITO a project of Academic Computing within the Department of Control and Computer Engineering at the Politecnico di Torino (http://hpc.polito.it) for providing computational resources. Moreover, the authors would like to thank the Intesa Sanpaolo team of cybersecurity, anti-fraud and data analytic solutions for providing the real dataset employed in the analysis through an agreement between Politecnico di Torino and Intesa Sanpaolo. The datasets analyzed during the current study are available from Intesa Sanpaolo on reasonable request and after finding a proper agreement.

Data Availability

The datasets analyzed during the current study are available on reasonable request and after finding a proper agreement with Intesa SanPaolo.

Owner

  • Name: Antonio Tudisco
  • Login: antotu
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