Davide Ferrari

Orcid: 0000-0002-4777-7234

Affiliations:
  • University of Parma, Quantum Software Laboratory (QSLab), Department of Engineering and Architecture, Italy


According to our database1, Davide Ferrari authored at least 13 papers between 2018 and 2026.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

Online presence:

On csauthors.net:

Bibliography

2026
Advanced Scheduling Strategies for Distributed Quantum Computing Jobs.
CoRR, February, 2026

2024
Distributed quantum computing: A survey.
Comput. Networks, 2024

Multi-Class Quantum Convolutional Neural Networks.
Proceedings of the 2024 Workshop on Quantum Search and Information Retrieval, 2024

Execution Management of Distributed Quantum Computing Jobs.
Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2024

Evaluation of Quantum and Hybrid Solvers for Combinatorial Optimization.
Proceedings of the 21st ACM International Conference on Computing Frontiers, 2024

2023
Compilation strategies for local and distributed quantum computing ; Strategie di compilazione per il calcolo quantistico locale e distribuito.
PhD thesis, 2023

2022
Distributed Quantum Computing: a Survey.
CoRR, 2022

Classical and Quantum Solvers for Joint Network/Servers Power Optimization.
CoRR, 2022

Enabling Location Based Services with Privacy and Integrity Protection in Untrusted Environments through Blockchain and Secure Computation.
Proceedings of the 4th IEEE International Conference on Trust, 2022

Noise-adaptive quantum compilation strategies evaluated with application-motivated benchmarks.
Proceedings of the CF '22: 19th ACM International Conference on Computing Frontiers, Turin, Italy, May 17, 2022

2021
Deterministic algorithms for compiling quantum circuits with recurrent patterns.
Quantum Inf. Process., 2021

2020
Compiler Design for Distributed Quantum Computing.
CoRR, 2020

2018
Demonstration of Envariance and Parity Learning on the IBM 16 Qubit Processor.
CoRR, 2018


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