Davide Pastorello

According to our database, Davide Pastorello authored at least 21 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

Network Security under Heterogeneous Cyber-Risk Profiles and Contagion.

Elisa Botteghi, Martino S. Centonze, Davide Pastorello, Daniele Tantari

CoRR, January, 2026

Efficient classical computation of the neural tangent kernel of quantum neural networks.

Anderson Melchor Hernandez, Davide Pastorello, Giacomo De Palma

Quantum, 2026

2025

A weighted quantum ensemble of homogeneous quantum classifiers.

Emiliano Tolotti, Enrico Blanzieri, Davide Pastorello

Quantum Mach. Intell., December, 2025

Enhancing Expressivity of Quantum Neural Networks Based on the SWAP test.

Sebastian Nagies, Emiliano Tolotti, Davide Pastorello, Enrico Blanzieri

CoRR, June, 2025

Mean-field limit from general mixtures of experts to quantum neural networks.

Anderson Melchor Hernandez, Davide Pastorello, Giacomo De Palma

CoRR, January, 2025

Consensus ranking by quantum annealing.

Daniele Franch, Enrico Zardini, Enrico Blanzieri, Davide Pastorello

CoRR, January, 2025

2024

A quantum k-nearest neighbors algorithm based on the Euclidean distance estimation.

Enrico Zardini, Enrico Blanzieri, Davide Pastorello

Quantum Mach. Intell., June, 2024

Ensembles of quantum classifiers.

Emiliano Tolotti, Enrico Zardini, Enrico Blanzieri, Davide Pastorello

Quantum Inf. Comput., March, 2024

Local Binary and Multiclass SVMs Trained on a Quantum Annealer.

Enrico Zardini, Amer Delilbasic, Enrico Blanzieri, Gabriele Cavallaro, Davide Pastorello

CoRR, 2024

Quantum Machine Learning: Perspectives in Cybersecurity.

Davide Pastorello

Proceedings of the Computer Safety, Reliability, and Security. SAFECOMP 2024 Workshops, 2024

Cyber Risk Propagation on Networks.

Elisa Botteghi, Davide Pastorello, Daniele Tantari

Proceedings of the Computer Safety, Reliability, and Security. SAFECOMP 2024 Workshops, 2024

2023

Evaluating the convergence of tabu enhanced hybrid quantum optimization.

Enrico Blanzieri, Davide Pastorello, Valter Cavecchia, Alexander S. Rumyantsev, Maria Maltseva

Quantum Inf. Process., May, 2023

A general learning scheme for classical and quantum Ising machines.

Ludwig Schmid, Enrico Zardini, Davide Pastorello

CoRR, 2023

Concise Guide to Quantum Machine Learning

Davide Pastorello

Springer, ISBN: 978-981-19-6896-9, 2023

2022

annealer.

Enrico Zardini, Massimo Rizzoli, Sebastiano Dissegna, Enrico Blanzieri, Davide Pastorello

Quantum Inf. Comput., 2022

Quantum annealing learning search implementations.

Andrea Bonomi, Thomas De Min, Enrico Zardini, Enrico Blanzieri, Valter Cavecchia, Davide Pastorello

Quantum Inf. Comput., 2022

Implementation and Empirical Evaluation of a Quantum Machine Learning Pipeline for Local Classification.

Enrico Zardini, Enrico Blanzieri, Davide Pastorello

CoRR, 2022

Reconstructing Bayesian Networks on a Quantum Annealer.

Enrico Zardini, Massimo Rizzoli, Sebastiano Dissegna, Enrico Blanzieri, Davide Pastorello

CoRR, 2022

2021

Learning adiabatic quantum algorithms over optimization problems.

Davide Pastorello, Enrico Blanzieri, Valter Cavecchia

Quantum Mach. Intell., 2021

A Quantum Binary Classifier based on Cosine Similarity.

Davide Pastorello, Enrico Blanzieri

Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2021

2019

Quantum annealing learning search for solving QUBO problems.

Davide Pastorello, Enrico Blanzieri

Quantum Inf. Process., 2019