Quantum social network analysis: Methodology, implementation, challenges, and future directions
Quantum social network analysis (QSNA) is a recent advancement in the interdisciplinary
field of quantum computing and social network analysis. This manuscript comprehensively …
field of quantum computing and social network analysis. This manuscript comprehensively …
Transitioning From Federated Learning to Quantum Federated Learning in Internet of Things: A Comprehensive Survey
Quantum Federated Learning (QFL) recently becomes a promising approach with the
potential to revolutionize Machine Learning (ML). It merges the established strengths of …
potential to revolutionize Machine Learning (ML). It merges the established strengths of …
Federated quantum long short-term memory (fedqlstm)
Quantum federated learning (QFL) can facilitate collaborative learning across multiple
clients using quantum machine learning (QML) models, while preserving data privacy …
clients using quantum machine learning (QML) models, while preserving data privacy …
Privacy-preserving quantum federated learning via gradient hiding
Distributed quantum computing, particularly distributed quantum machine learning, has
gained substantial prominence for its capacity to harness the collective power of distributed …
gained substantial prominence for its capacity to harness the collective power of distributed …
Hybrid quantum image classification and federated learning for hepatic steatosis diagnosis
L Lusnig, A Sagingalieva, M Surmach, T Protasevich… - Diagnostics, 2024 - mdpi.com
In the realm of liver transplantation, accurately determining hepatic steatosis levels is crucial.
Recognizing the essential need for improved diagnostic precision, particularly for optimizing …
Recognizing the essential need for improved diagnostic precision, particularly for optimizing …
Advances and open challenges in federated learning with foundation models
Abstract The integration of Foundation Models (FMs) with Federated Learning (FL) presents
a transformative paradigm in Artificial Intelligence (AI), offering enhanced capabilities while …
a transformative paradigm in Artificial Intelligence (AI), offering enhanced capabilities while …
Federated Learning with Quantum Computing and Fully Homomorphic Encryption: A Novel Computing Paradigm Shift in Privacy-Preserving ML
The widespread deployment of products powered by machine learning models is raising
concerns around data privacy and information security worldwide. To address this issue …
concerns around data privacy and information security worldwide. To address this issue …
Dimensionality Reduction for Data Analysis With Quantum Feature Learning
SR Sihare - Wiley Interdisciplinary Reviews: Data Mining and …, 2025 - Wiley Online Library
To improve data analysis and feature learning, this study compares the effectiveness of
quantum dimensionality reduction (qDR) techniques to classical ones. In this study, we …
quantum dimensionality reduction (qDR) techniques to classical ones. In this study, we …
Variational quantum circuit and quantum key distribution-based quantum federated learning: A case of smart grid dynamic security assessment
This paper proposes a hybrid Quantum Federated Learning (QFL) method, called QQFL, a
revolutionary approach for Dynamic Security Assessment (DSA) optimized for modern smart …
revolutionary approach for Dynamic Security Assessment (DSA) optimized for modern smart …
ESQFL: Digital Twin-Driven Explainable and Secured Quantum Federated Learning for Voltage Stability Assessment in Smart Grids
Voltage stability remains a pivotal concern in power systems, especially with the integration
of renewable energy sources and high-demand loads that use induction motors. Recent …
of renewable energy sources and high-demand loads that use induction motors. Recent …