arXiv Machine Learning
Quantum Sparse Autoencoders for Q-Matrix Estimation in Cognitive Diagnosis
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Hybrid Classical-Quantum (HCQ) Alzheimer's Classification via Supervised $\beta$-VAE and Quantum Kernels
arXiv:2606. 14194v1 Announce Type: cross Abstract: This paper presents a two-stage Hybrid Classical-Quantum (HCQ) pipeline for binary Alzheimer's disease (AD) classification from 3D T1-weighted structural MRI volumes, where the classical and quantum components are designed to complement each other rather than operate independently.
arXiv Machine Learning
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Is data-efficient learning feasible with quantum models?
arXiv:2508. 19437v2 Announce Type: replace-cross Abstract: The importance of analyzing nontrivial datasets when testing quantum machine learning (QML) models is becoming increasingly prominent in literature, yet a cohesive framework for understanding dataset characteristics remains elusive.
arXiv Machine Learning
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Quantum Spectral Model: Data Reuploading with Input-Conditioned Frequency Support
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arXiv Machine Learning
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Tailor Made Embeddings for Quantum Machine Learning
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Comparative Study of Quantum and Classical Machine Learning Models in Binary Classification
arXiv:2609.23476v1 Announce Type: cross Abstract: A potential path forward is Quantum Machine Learning (QML), which aims to leverage quantum computing in conjunction with classical machine learning t...
arXiv AI
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Compression-Driven Anomaly Detection in Brain MRI Using an Interpretable Quantum Autoencoder
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