4 citations · 4 across the 3 of their papers we have counts for
3 papers
Train on classical, deploy on quantum: scaling generative quantum machine learning to a thousand qubits
Erik Recio-Armengol, Shahnawaz Ahmed, Joseph Bowles
We propose an approach to generative quantum machine learning that overcomes the fundamental scaling issues of variational quantum circuits. The core idea is to use a class of gene…
Learning complexity gradually in quantum machine learning models
Erik Recio-Armengol, Franz J. Schreiber, Jens Eisert +1
Quantum machine learning is an emergent field that continues to draw significant interest for its potential to offer improvements over classical algorithms in certain areas. Howeve…
Single-shot quantum machine learning
Erik Recio-Armengol, Jens Eisert, Johannes Jakob Meyer
Quantum machine learning aims to improve learning methods through the use of quantum computers. If it is to ever realize its potential, many obstacles need to be overcome. A partic…