arXiv Machine Learning By Mariano Caruso, Daniel Ruiz, Alejandro Giraldo, Guido Bellomo

$\mathtt{Q^2SAR}$: overcoming classical bottlenecks in drug discovery via quantum multiple kernel learning

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arXiv:2607. 11701v1 Announce Type: cross Abstract: Quantitative Structure-Activity Relationship ($\mathtt{QSAR}$) modeling is a foundational computational methodology in early-stage drug discovery, heavily relied upon for predicting compound toxicity, bioavailability, and therapeutic potential.

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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.

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Hybrid Classical-Quantum (HCQ) Alzheimer's Classification via Supervised $\beta$-VAE and Quantum Kernels

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