Quantum anomaly detection in real scarce data

arXiv:2610.09635 · quant-ph, cs.LG · Submitted 2026-10-07 · Read on arXiv

quant-ph, cs.LG

Submitted: 2026-10-07

Updated: 2026-10-07

Code: https://github.com/clayton-h-costa/pv_fault_dataset

Terminology

• Entanglement — 7× in this paper · explained in 4 episodes
• Predictive Maintenance — 7× in this paper · explained in 2 episodes
• Accuracy — 6× in this paper · explained in 1 episode
• Convolutional Neural Network — 4× in this paper
• Recurrent Neural Network — 4× in this paper
• Transformer — 4× in this paper · explained in 2 episodes
• Hybrid Models — 3× in this paper · explained in 2 episodes
• Long Short-Term Memory — 3× in this paper
• Attention Mechanism — 2× in this paper · explained in 3 episodes
• Benchmark — 2× in this paper · explained in 2 episodes
• Generalization — 2× in this paper · explained in 13 episodes
• Latent Representation — 2× in this paper · explained in 2 episodes
• Parameter Efficiency — 2× in this paper · explained in 3 episodes
• Quantum Circuits — 2× in this paper · explained in 2 episodes
• Abundance — 1× in this paper · explained in 1 episode
• Adaptability — 1× in this paper · explained in 1 episode
• Aggregation — 1× in this paper · explained in 1 episode
• Aggregation Function — 1× in this paper · explained in 1 episode
• Benchmarking — 1× in this paper · explained in 3 episodes
• Data Augmentation — 1× in this paper · explained in 7 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Objective Function — 1× in this paper · explained in 2 episodes
• One-Class Support Vector Machine — 1× in this paper
• Quantum Neural Networks — 1× in this paper
• Reconstruction Error — 1× in this paper · explained in 2 episodes
• Transformer Architecture — 1× in this paper · explained in 2 episodes

Sources

• Deep Learning for Anomaly Detection: A Survey
• DASVDD: Deep Autoencoding Support Vector Data Descriptor for Anomaly Detection
• Recurrent Neural Networks (RNNs): A gentle Introduction and Overview
• Unsupervised quantum machine learning for fraud detection
• Quantum implementation of an artificial feed-forward neural network
• Quantum Convolutional Neural Networks
• Implementation Guidelines and Innovations in Quantum LSTM Networks
• A Hybrid Quantum-Classical Neural Network Architecture for Binary Classification
• Data re-uploading in Quantum Machine Learning for time series: application to traffic forecasting
• Understanding intermediate layers using linear classifier probes
• PennyLane: Automatic differentiation of hybrid quantum-classical computations

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