Quantitative Universal Approximation for Noisy Quantum Neural Networks

Lukas Gonon, Antoine Jacquier, Marcel Mordarski

We provide here a universal approximation theorem with precise quantitative error bounds for noisy quantum neural networks. We focus on applications to Quantitative Finance, where…