25 citations · 27 across the 7 of their papers we have counts for
7 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…
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…
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…
A Laplacian-based Quantum Graph Neural Network for Semi-Supervised Learning
Hamed Gholipour, Farid Bozorgnia, Kailash Hambarde +5
Laplacian learning method is a well-established technique in classical graph-based semi-supervised learning, but its potential in the quantum domain remains largely unexplored. Thi…
Empowering Credit Scoring Systems with Quantum-Enhanced Machine Learning
Javier Mancilla, André Sequeira, Tomas Tagliani +2
Quantum Kernels are projected to provide early-stage usefulness for quantum machine learning. However, highly sophisticated classical models are hard to surpass without losing inte…
A preprocessing perspective for quantum machine learning classification advantage using NISQ algorithms
Javier Mancilla, Christophe Pere
Quantum Machine Learning (QML) hasn't yet demonstrated extensively and clearly its advantages compared to the classical machine learning approach. So far, there are only specific c…