scholar.google.com › citations
Jun 15, 2020 · In this work, we introduce a general model framework that reproduces a quantum state equivalent to the output of a classical Single Layer ...
To summarise, the variational algorithm described above allows reproducing a classical Neural Network with one hidden layer on a quantum computer. In particular ...
This work introduces a novel variational algorithm for quantum Single Layer Perceptron and designs a quantum circuit to perform linear combinations in ...
People also ask
What is a variational quantum algorithm?
Which algorithm is used in quantum computing?
What algorithms are used to train neural networks?
What is variational quantum classifier?
Sep 12, 2022 · The algorithm consists of five parts, including the preparation of quantum states, the application of linear superposition circuits, the ...
Aug 2, 2023 · We introduce a general framework called neural network (NN) encoded variational quantum algorithms (VQAs), or NN-VQA for short, to address the challenges of ...
Jan 26, 2024 · We introduce a general framework called neural-network- (NN) encoded variational quantum algorithms (VQAs), or NNVQA for short, ...
Dec 15, 2022 · Previous results have shown that unlike the case in classical neural networks, variational quantum models are often not trainable. The most ...
Mar 10, 2023 · The objective of this paper is to investigate how training of quantum neural network (QNNs) can be done using quantum optimization algorithms.
This paper establishes a new QNN model, the optimization process adopts efficient quantum particle swarm optimization, and tentatively adds a quantum ...
Jun 15, 2020 · In particular, we design a quantum circuit to perform linear combinations in superposition and discuss adaptations to classification and ...