3 papers
quant-ph2026
Enhancing Expressivity of Quantum Neural Networks Based on the SWAP test
Sebastian Nagies, Emiliano Tolotti, Davide Pastorello +1
Quantum neural networks (QNNs) based on parametrized quantum circuits are promising candidates for machine learning applications, yet many architectures lack clear connections to c…
quant-ph2025
A weighted quantum ensemble of homogeneous quantum classifiers
Emiliano Tolotti, Enrico Blanzieri, Davide Pastorello
Ensemble methods in machine learning aim to improve prediction accuracy by combining multiple models. This is achieved by ensuring diversity among predictors to capture different d…
cs.DC2024
cuVegas: Accelerate Multidimensional Monte Carlo Integration through a Parallelized CUDA-based Implementation of the VEGAS Enhanced Algorithm
Emiliano Tolotti, Anas Jnini, Flavio Vella +1
This paper introduces cuVegas, a CUDA-based implementation of the Vegas Enhanced Algorithm (VEGAS+), optimized for multi-dimensional integration in GPU environments. The VEGAS+ alg…