6 papers
Quantum Deep Sets and Sequences
Vladimir Vargas-Calderón
This paper introduces the quantum deep sets model, expanding the quantum machine learning tool-box by enabling the possibility of learning variadic functions using quantum systems.…
: an automated algebraic solution for high-order quantum systems
D. Martínez-Tibaduiza, Vladimir Vargas-Calderón, J. G. Dueñas +2
Many significant quantum physical systems are characterized by Hamiltonians expressible as a linear combination of time-independent generators of a closed Lie algebra, $\hat{H}(t)=…
Quantum generative classification with mixed states
Diego H. Useche, Sergio Quiroga-Sandoval, Sebastian L. Molina +3
Classification can be performed using either a discriminative or a generative learning approach. Discriminative learning consists of constructing the conditional probability of the…
Arbitrary state preparation in quantum harmonic oscillators using neural networks
Nicolas Parra-A, Vladimir Vargas-Calderón, Herbert Vinck-Posada
Preparing quantum states is a fundamental task in various quantum algorithms. In particular, state preparation in quantum harmonic oscillators (HOs) is crucial for the manipulation…
Variational decision diagrams for quantum-inspired machine learning applications
Vladimir Vargas-Calderón, Santiago Acevedo-Mancera, Herbert Vinck-Posada
Decision diagrams (DDs) have emerged as an efficient tool for simulating quantum circuits due to their capacity to exploit data redundancies in quantum states and quantum operation…
MEMO-QCD: Quantum Density Estimation through Memetic Optimisation for Quantum Circuit Design
Juan E. Ardila-García, Vladimir Vargas-Calderón, Fabio A. González +2
This paper presents a strategy for efficient quantum circuit design for density estimation. The strategy is based on a quantum-inspired algorithm for density estimation and a circu…