176 citations · 354 across the 7 of their papers we have counts for
9 papers
Comment on the Quantum Supremacy Claim by Google
Anirudh Reddy, Benjamin Perez-Garcia, Adenilton Jose da Silva +1
Quantum computation promises to execute certain computational tasks on time scales much faster than any known algorithm on an existing classical computer, for example calculating t…
Configurable sublinear circuits for quantum state preparation
Israel F. Araujo, Daniel K. Park, Teresa B. Ludermir +3
The theory of quantum algorithms promises unprecedented benefits of harnessing the laws of quantum mechanics for solving certain computational problems. A persistent obstacle to us…
A divide-and-conquer algorithm for quantum state preparation
Israel F. Araujo, Daniel K. Park, Francesco Petruccione +1
Advantages in several fields of research and industry are expected with the rise of quantum computers. However, the computational cost to load classical data in quantum computers c…
Quantum ensemble of trained classifiers
Ismael C. S. Araujo, Adenilton J. da Silva
Through superposition, a quantum computer is capable of representing an exponentially large set of states, according to the number of qubits available. Quantum machine learning is…
Quantum One-class Classification With a Distance-based Classifier
Nicolas M. de Oliveira, Lucas P. de Albuquerque, Wilson R. de Oliveira +2
The advancement of technology in Quantum Computing has brought possibilities for the execution of algorithms in real quantum devices. However, the existing errors in the current qu…
Parametric Probabilistic Quantum Memory
Rodrigo S. Sousa, Priscila G. M. dos Santos, Tiago M. L. Veras +2
Probabilistic Quantum Memory (PQM) is a data structure that computes the distance from a binary input to all binary patterns stored in superposition on the memory. This data struct…
Quantum enhanced cross-validation for near-optimal neural networks architecture selection
Priscila G. M. dos Santos, Rodrigo S. Sousa, Ismael C. S. Araujo +1
This paper proposes a quantum-classical algorithm to evaluate and select classical artificial neural networks architectures. The proposed algorithm is based on a probabilistic quan…
Quantum perceptron over a field and neural network architecture selection in a quantum computer
Adenilton J. da Silva, Teresa B. Ludermir, Wilson R. de Oliveira
In this work, we propose a quantum neural network named quantum perceptron over a field (QPF). Quantum computers are not yet a reality and the models and algorithms proposed in thi…
Weightless neural network parameters and architecture selection in a quantum computer
Adenilton J. da Silva, Wilson R. de Oliveira, Teresa B. Ludermir
Training artificial neural networks requires a tedious empirical evaluation to determine a suitable neural network architecture. To avoid this empirical process several techniques…