most citedEmpowering Credit Scoring Systems with Quantum-Enhanced Machine Learning

2 citations · 2 across the 5 of their papers we have counts for

collaborators

5 papers

quant-ph2024

A hybrid classical-quantum approach to highly constrained Unit Commitment problems

Bruna Salgado, André Sequeira, Luis Paulo Santos

The unit commitment (UC) problem stands as a critical optimization challenge in the electrical power industry. It is classified as NP-hard, placing it among the most intractable pr…

cs.LG2024

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…

quant-ph2024

Trainability issues in quantum policy gradients

André Sequeira, Luis Paulo Santos, Luis Soares Barbosa

This research explores the trainability of Parameterized Quantum circuit-based policies in Reinforcement Learning, an area that has recently seen a surge in empirical exploration.…

q-fin.RM20242 cited

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…

quant-ph2024

On Quantum Natural Policy Gradients

André Sequeira, Luis Paulo Santos, Luis Soares Barbosa

This research delves into the role of the quantum Fisher Information Matrix (FIM) in enhancing the performance of Parameterized Quantum Circuit (PQC)-based reinforcement learning a…