Time Series forecasting with Quantum Neural Networks

Abstract

In this work we explore the use of Quantum Computing for Time Series forecasting. More speci cally, we design Variational Quantum Circuits as the quantum analogy of feedforward Artificial Neural Networks, and use a quantum neural network pipeline to perform time series forecasting tasks. According to our experiments, our study suggests that Quantum Neural Networks are able to improve results in error prediction while maintaining a lower number of parameters than its classical machine learning counterpart.