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Quantum computing for pattern classification
Maria Schuld, Ilya Sinayskiy, Francesco Petruccione
It is well known that for certain tasks, quantum computing outperforms classical computing. A growing number of contributions try to use this advantage in order to improve or exten…
Simulating a perceptron on a quantum computer
Maria Schuld, Ilya Sinayskiy, Francesco Petruccione
Perceptrons are the basic computational unit of artificial neural networks, as they model the activation mechanism of an output neuron due to incoming signals from its neighbours.…
An introduction to quantum machine learning
M. Schuld, I. Sinayskiy, F. Petruccione
Machine learning algorithms learn a desired input-output relation from examples in order to interpret new inputs. This is important for tasks such as image and speech recognition o…
The quest for a Quantum Neural Network
M. Schuld, I. Sinayskiy, F. Petruccione
With the overwhelming success in the field of quantum information in the last decades, the "quest" for a Quantum Neural Network (QNN) model began in order to combine quantum comput…
Quantum walks on graphs representing the firing patterns of a quantum neural network
Maria Schuld, Ilya Sinayskiy, Francesco Petruccione
Quantum walks have been shown to be fruitful tools in analysing the dynamic properties of quantum systems. This article proposes to use quantum walks as an approach to Quantum Neur…