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Implementing quantum machine learning models for financial applications

Published on:

15 August 2023

Primary Category:

Quantum Physics

Paper Authors:

Santanu Ganguly

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Key Details

qGAN and QCBM are promising quantum ML models for finance

qGAN uses a quantum generator and classical discriminator

QCBM directly samples the underlying quantum state

Real financial data was used to train and test the models

The quantum models performed well on the financial data

AI generated summary

Implementing quantum machine learning models for financial applications

This paper explores using quantum machine learning models like quantum generative adversarial networks (qGAN) and quantum circuit Born machines (QCBM) for financial applications like options pricing. Real financial data is used to train and test these models in simulated quantum computing environments. The quantum models show promise for efficiently modeling financial data, though more research is still needed.

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