Mixed Quantum–Classical Method for Fraud Detection With Quantum Feature Selection-Reference-Cited by-同舟云学术

Mixed Quantum–Classical Method for Fraud Detection With Quantum Feature Selection

Published:2022 Issue: Volume:3 Page:1-12
ISSN:2689-1808
Container-title:IEEE Transactions on Quantum Engineering
language:
Short-container-title:IEEE Trans. Quantum Eng.

Author:

Grossi Michele¹^ORCID,Ibrahim Noelle²^ORCID,Radescu Voica³^ORCID,Loredo Robert⁴^ORCID,Voigt Kirsten⁵^ORCID,von Altrock Constantin⁵,Rudnik Andreas⁵

Affiliation:

1. European Organization for Nuclear Research (CERN), Geneva, Switzerland

2. IBM Quantum, IBM, Markham, ON, Canada

3. IBM Quantum, IBM Deutschland Research & Development GmbH, Böblingen, Germany

4. IBM Quantum, IBM Corp, Coral Gables, FL, USA

5. IRIS Analytics GmbH, Urbar, Germany

Funder

CERN Quantum Technology Initiative

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Mechanical Engineering,Engineering (miscellaneous),Condensed Matter Physics,Computer Science (miscellaneous),Software

Link

http://xplorestaging.ieee.org/ielx7/8924785/9669178/09915517.pdf?arnumber=9915517

Reference28 articles.

1. Efficient Discrete Feature Encoding for Variational Quantum Classifier

2. The power of quantum neural networks

3. Quantum Machine Learning Algorithms for Drug Discovery Applications

4. Classification of the MNIST data set with quantum slow feature analysis

5. Quantum machine learning: a classical perspective

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