Imperial College London Proposes Optimal Training of Variational Quantum Algorithms Without Barren Plateaus | Synced
Imperial College London researchers show how to optimally train a variational quantum algorithm to represent quantum states and propose a stable variant of the quantum natural gradient, a generaliz...
Source: Synced | AI Technology & Industry Review
Imperial College London researchers show how to optimally train a variational quantum algorithm to represent quantum states and propose a stable variant of the quantum natural gradient, a generalized quantum natural gradient that can be trained free of barren plateaus.
