121 citations · 205 across the 6 of their papers we have counts for
6 papers
A Framework for Demonstrating Practical Quantum Advantage: Racing Quantum against Classical Generative Models
Mohamed Hibat-Allah, Marta Mauri, Juan Carrasquilla +1
Generative modeling has seen a rising interest in both classical and quantum machine learning, and it represents a promising candidate to obtain a practical quantum advantage in th…
Do Quantum Circuit Born Machines Generalize?
Kaitlin Gili, Mohamed Hibat-Allah, Marta Mauri +2
In recent proposals of quantum circuit models for generative tasks, the discussion about their performance has been limited to their ability to reproduce a known target distributio…
Generalization Metrics for Practical Quantum Advantage in Generative Models
Kaitlin Gili, Marta Mauri, Alejandro Perdomo-Ortiz
As the quantum computing community gravitates towards understanding the practical benefits of quantum computers, having a clear definition and evaluation scheme for assessing pract…
Quantum algorithm for credit valuation adjustments
Javier Alcazar, Andrea Cadarso, Amara Katabarwa +4
Quantum mechanics is well known to accelerate statistical sampling processes over classical techniques. In quantitative finance, statistical samplings arise broadly in many use cas…
FLIP: A flexible initializer for arbitrarily-sized parametrized quantum circuits
Frederic Sauvage, Sukin Sim, Alexander A. Kunitsa +3
When compared to fault-tolerant quantum computational strategies, variational quantum algorithms stand as one of the candidates with the potential of achieving quantum advantage fo…
NetKet: A Machine Learning Toolkit for Many-Body Quantum Systems
Giuseppe Carleo, Kenny Choo, Damian Hofmann +15
We introduce NetKet, a comprehensive open source framework for the study of many-body quantum systems using machine learning techniques. The framework is built around a general and…