23 citations · 35 across the 5 of their papers we have counts for
9 papers
Qubit seriation: Improving data-model alignment using spectral ordering
Atithi Acharya, Manuel Rudolph, Jing Chen +2
With the advent of quantum and quantum-inspired machine learning, adapting the structure of learning models to match the structure of target datasets has been shown to be crucial f…
ORQVIZ: Visualizing High-Dimensional Landscapes in Variational Quantum Algorithms
Manuel S. Rudolph, Sukin Sim, Asad Raza +5
Variational Quantum Algorithms (VQAs) are promising candidates for finding practical applications of near to mid-term quantum computers. There has been an increasing effort to stud…
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…
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…