Quantum Conformal Prediction for Reliable Uncertainty Quantification in Quantum Machine Learning

Quantum machine learning is a promising programming paradigm for the optimization of quantum algorithms in the current era of noisy intermediate-scale quantum computers. A fundamental challenge in quantum machine learning is generalization, as the designer targets performance under testing conditions while having access only to limited training data. Existing generalization analyses, while identifying important general […]

Prediction of Solar Irradiance One Hour Ahead Based on Quantum Long Short-Term Memory Network

The short-term forecasting of photovoltaic (PV) power generation ensures the scheduling and dispatching of electrical power, helps design a PV-integrated energy management system, and enhances the security of grid operation. However, due to the randomness of solar energy, the output of the PV system will fluctuate, which will affect the safe operation of the grid. […]