Research outputs
Selected research outputs
- Accounting for the Impact of Real-World Data and Costs in Autonomous Cyber Defence (Conference Paper - 2025)
- Stone Soup Goes NUTS: Adding Proposals and The No-U-Turn Sampler to Stone Soup (Conference Paper - 2025)
- Defending the unknown: Exploring reinforcement learning agents' deployment in realistic, unseen networks (Conference Paper - 2023)
- The BAHAMAS project: evaluating the accuracy of the halo model in predicting the non-linear matter power spectrum (Journal article - 2021)
2025
Accounting for the Impact of Real-World Data and Costs in Autonomous Cyber Defence
Neal, A., Acuto, A., Green, P. L., Lear, C., Hare, N., & Maskell, S. (2025). Accounting for the Impact of Real-World Data and Costs in Autonomous Cyber Defence. In 2025 IEEE INTERNATIONAL CONFERENCE ON CYBER SECURITY AND RESILIENCE, CSR (pp. 399-406). doi:10.1109/CSR64739.2025.11130046
Stone Soup Goes NUTS: Adding Proposals and The No-U-Turn Sampler to Stone Soup
Acuto, A., Vladimirov, L., Varsi, A., Horridge, P., & Maskell, S. (2025). Stone Soup Goes NUTS: Adding Proposals and The No-U-Turn Sampler to Stone Soup. In 2025 28TH INTERNATIONAL CONFERENCE ON INFORMATION FUSION, FUSION (pp. 480-487). Retrieved from https://www.webofscience.com/
2024
2023
Defending the unknown: Exploring reinforcement learning agents' deployment in realistic, unseen networks
Acuto, A., Maskell, S., & Jack, D. (2023). Defending the unknown: Exploring reinforcement learning agents' deployment in realistic, unseen networks. In Ceur Workshop Proceedings Vol. 3652 (pp. 22-35).
2021
The BAHAMAS project: evaluating the accuracy of the halo model in predicting the non-linear matter power spectrum
Acuto, A., McCarthy, I. G., Kwan, J., Salcido, J., Stafford, S. G., & Font, A. S. (2021). The BAHAMAS project: evaluating the accuracy of the halo model in predicting the non-linear matter power spectrum. MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY, 508(3), 3519-3534. doi:10.1093/mnras/stab2834