Quantum reservoir computing with distributed architectures reduces time-series forecasting errors by up to 78.8% MAE and 72.3% RMSE in NISQ simulations compared to classical methods.
Feedback-driven quantum reservoir computing for time-series analysis
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Scalable Quantum Reservoir Computing over Distributed Quantum Architectures
Quantum reservoir computing with distributed architectures reduces time-series forecasting errors by up to 78.8% MAE and 72.3% RMSE in NISQ simulations compared to classical methods.