377 citations · 393 across the 4 of their papers we have counts for
5 papers
Re-QGAN: an optimized adversarial quantum circuit learning framework
Sandra Nguemto, Vicente Leyton-Ortega
Adversarial learning represents a powerful technique for generating data statistics. Its successful implementation in quantum computational platforms is not straightforward due to…
Classical versus Quantum Models in Machine Learning: Insights from a Finance Application
Javier Alcazar, Vicente Leyton-Ortega, Alejandro Perdomo-Ortiz
Although several models have been proposed towards assisting machine learning (ML) tasks with quantum computers, a direct comparison of the expressive power and efficiency of class…
Entanglement types for two-qubit states with real amplitudes
Oscar Perdomo, Vicente Leyton-Ortega, Alejandro Perdomo-Ortiz
We study the set of two-qubit pure states with real amplitudes and their geometrical representation in the three-dimensional sphere. In this representation, we show that the maxima…
Robust Implementation of Generative Modeling with Parametrized Quantum Circuits
Vicente Leyton-Ortega, Alejandro Perdomo-Ortiz, Oscar Perdomo
Although the performance of hybrid quantum-classical algorithms is highly dependent on the selection of the classical optimizer and the circuit ansatz, a robust and thorough assess…
A generative modeling approach for benchmarking and training shallow quantum circuits
Marcello Benedetti, Delfina Garcia-Pintos, Oscar Perdomo +3
Hybrid quantum-classical algorithms provide ways to use noisy intermediate-scale quantum computers for practical applications. Expanding the portfolio of such techniques, we propos…