4 papers
The Fourier Wall: Why Public Tabular Datasets Refuse Quantum Advantage, and a Certified Recipe for Where It Lives
Javier Mancilla, Tomás Tagliani
Across public tabular benchmarks, quantum machine-learning (QML) models usually lose to carefully tuned classical baselines. We argue that this is a structural property of the data…
A Mixture-of-Experts Framework for Practical Hybrid-Quantum Models in Credit Card Fraud Detection
Rodrigo Chaves, Kunal Kumar, Bruno Chagas +4
This paper investigates whether hybrid quantum-classical machine learning can deliver practical improvements in financial fraud detection performance for card-based and other payme…
Q2SAR: A Quantum Multiple Kernel Learning Approach for Drug Discovery
Alejandro Giraldo, Daniel Ruiz, Mariano Caruso +2
Quantitative Structure-Activity Relationship (QSAR) modeling is a cornerstone of computational drug discovery. This research demonstrates the successful application of a Quantum Mu…
Enhancement of Quantum Semi-Supervised Learning via Improved Laplacian and Poisson Methods
Hamed Gholipour, Farid Bozorgnia, Hamzeh Mohammadigheymasi +5
This paper develops a hybrid quantum approach for graph-based semi-supervised learning to enhance performance in scenarios where labeled data is scarce. We introduce two enhanced q…