Quantum Federated Learning (QFL) is an emerging concept that aims to unfold federated
learning (FL) over quantum networks, enabling collaborative quantum model training along …

Quantum Federated Learning (QFL) is an emerging interdisciplinary field that merges the
principles of Quantum Computing (QC) and Federated Learning (FL), with the goal of …

As the development of quantum computing hardware is on the rise, its potential application
to various research areas has been investigated, including to machine learning. Recently …

Quantum federated learning (QFL) is a novel framework that integrates the advantages of
classical federated learning (FL) with the computational power of quantum technologies …

Quantum Federated Learning (QFL) has gained significant attention due to quantum
computing and machine learning advancements. As the demand for QFL continues to surge …

In this study, we explore the innovative domain of Quantum Federated Learning (QFL) as a
framework for training Quantum Machine Learning (QML) models via distributed networks …

Quantum federated learning (QFL) has recently received increasing attention, where
quantum neural networks (QNNs) are integrated into federated learning (FL). In contrast to …

Quantum federated learning (QFL) enables collaborative training of a quantum machine
learning (QML) model among multiple clients possessing quantum computing capabilities …

Recent advancements in quantum computing, alongside successful deployments of
quantum communication, hold promises for revolutionizing mobile networks. While Quantum …

Quantum Federated Learning (QFL) recently becomes a promising approach with the
potential to revolutionize Machine Learning (ML). It merges the established strengths of …