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Modeling Quantum Federated Autoencoder for Anomaly Detection in IoT Networks

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1 SIGNALFIRST DETECTED 26 March 2026
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26 Mar
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Other feeds and industry voices
29 Jun
Compression-Driven Anomaly Detection in Brain MRI Using an Interpretable Quantum Autoencoder

arXiv:2606.27411v1 Announce Type: cross Abstract: We study a quantum autoencoder (QAE) for compression-driven anomaly detection in brain MRI data. The approach leverages angle

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2 Sept
A Stable Aggregation Method for Quantum Federated Learning

arXiv:2609.00356v1 Announce Type: new Abstract: Quantum federated learning (QFL) enables clients to train quantum neural network (QNN) models without sharing private data. We find

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26 Mar
Q-AGNN: Quantum-Enhanced Attentive Graph Neural Network for Intrusion Detection

arXiv:2603.22365v1 Announce Type: cross Abstract: With the rapid growth of interconnected devices, accurately detecting malicious activities in network traffic has become

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27 Mar
Agentic Trust Coordination for Federated Learning through Adaptive Thresholding and Autonomous Decision Making in Sustainable and Resilient Industrial Networks

arXiv:2603.25334v1 Announce Type: new Abstract: Distributed intelligence in industrial networks increasingly integrates sensing, communication, and computation across

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30 Apr
Privacy-Preserving Federated Learning Framework for Distributed Chemical Process Optimization

arXiv:2604.26073v1 Announce Type: cross Abstract: Industrial chemical plants often operate under strict data confidentiality constraints, making centralized data-driven process

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