Quantum machine learning beyond kernel methods - Sofiene Jerbi; Lukas J. Fiderer; Hendrik Poulsen Nautrup; Jonas M. Kübler; Hans J. Briegel; Vedran Dunjko (Nature Communications, 2023)
Comparing the capabilities of different quantum machine learning protocols is difficult. Here, the authors show that different learning models based on parametrized quantum circuits can all be seen as quantum linear models, thus driving general conclusions on their resource requirements and capabilities.