Abstract The Internet of Things (IoT) has revolutionized various sectors by enabling
seamless device interaction. However, the proliferation of IoT devices has also raised …

Quantum social network analysis (QSNA) is a recent advancement in the interdisciplinary
field of quantum computing and social network analysis. This manuscript comprehensively …

Quantum federated learning (QFL) can facilitate collaborative learning across multiple
clients using quantum machine learning (QML) models, while preserving data privacy …

In this work, we introduce the Federated Quantum-Train (QT) framework, which integrates
the QT model into federated learning to leverage quantum computing for distributed learning …

A major concern of deep learning models is the large amount of data that is required to build
and train them, much of which is reliant on sensitive and personally identifiable information …

Federated Learning has emerged as a revolutionary technology in Machine Learning (ML),
enabling collaborative training of models in a distributed environment while ensuring privacy …

In the realm of intelligent healthcare, there is a growing ambition to reshape medical
services through the integration of artificial intelligence (AI). However, conventional machine …

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 …

Drug discovery and development is a highly complex and costly endeavor, typically
requiring over a decade and substantial financial investment to bring a new drug to market …

Quantum networks (QNs) relying on free-space optical (FSO) quantum channels can support
quantum applications in environments wherein establishing an optical fiber infrastructure is …