All Outputs (2)

Training neural networks with universal adiabatic quantum computing (2024)
Journal Article
Abel, S., Criado, J. C., & Spannowsky, M. (in press). Training neural networks with universal adiabatic quantum computing. Frontiers in Artificial Intelligence, 7, Article 1368569. https://doi.org/10.3389/frai.2024.1368569

The training of neural networks (NNs) is a computationally intensive task requiring significant time and resources. This article presents a novel approach to NN training using adiabatic quantum computing (AQC), a paradigm that leverages the principle... Read More about Training neural networks with universal adiabatic quantum computing.

Completely quantum neural networks (2022)
Journal Article
Abel, S., Criado, J. C., & Spannowsky, M. (2022). Completely quantum neural networks. Physical Review A, 106(2), Article 022601. https://doi.org/10.1103/physreva.106.022601

Artificial neural networks are at the heart of modern deep learning algorithms. We describe how to embed and train a general neural network in a quantum annealer without introducing any classical element in training. To implement the network on a sta... Read More about Completely quantum neural networks.