Publications
Selected publications
- Simulation to optimize the laboratory diagnosis of bacteremia. (Journal article - 2024)
- Bayesian Calibration to Address the Challenge of Antimicrobial Resistance: A Review (Journal article - 2024)
- Refining epidemiological forecasts with simple scoring rules (Journal article - 2022)
- Enhanced SMC<sup>2</sup>: Leveraging Gradient Information from Differentiable Particle Filters Within Langevin Proposals (Conference Paper - 2024)
- An O(log<sub>2</sub> N) SMC<sup>2</sup> Algorithm on Distributed Memory with an Approx. Optimal L-Kernel (Conference Paper - 2023)
- Inference of Stochastic Disease Transmission Models Using Particle-MCMC and a Gradient Based Proposal (Conference Paper - 2022)
- Efficient Learning of the Parameters of Non-Linear Models using Differentiable Resampling in Particle Filters (Journal article - 2022)
2025
Detecting Simulated Nosocomial Disease Outbreaks with Sequential Monte Carlo Methods
Rosato, D. C. (2025). Detecting Simulated Nosocomial Disease Outbreaks with Sequential Monte Carlo Methods. International Journal of Infectious Diseases, 152, 107544. doi:10.1016/j.ijid.2024.107544
Diagnostics-linked Antimicrobial Surveillance: A Route to Patient-Centred Microbiology Diagnostics?
Howard, D. A., Brookfield, D. C., Rosato, D. C., Velluva, D. A., Gerada, D. A., & Hope, P. W. (2025). Diagnostics-linked Antimicrobial Surveillance: A Route to Patient-Centred Microbiology Diagnostics?. International Journal of Infectious Diseases, 152, 107554. doi:10.1016/j.ijid.2024.107554
Gastro-intestinal transmission and colonisation of pathogenic bacteria: calibration of an agent-based model
Gerada, D. A., Rosato, D. C., Howard, D. A., Green, D. P. L., & Hope, D. W. (2025). Gastro-intestinal transmission and colonisation of pathogenic bacteria: calibration of an agent-based model. International Journal of Infectious Diseases, 152, 107600. doi:10.1016/j.ijid.2024.107600
2024
Parameterizing Hierarchical Particle Filters with Concept Drift for Time-varying Parameter Estimation
Murphy, J., Rosato, C., Millard, A., & Maskell, S. (2024). Parameterizing Hierarchical Particle Filters with Concept Drift for Time-varying Parameter Estimation. In 2024 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC) (pp. 1-6). IEEE. doi:10.1109/apsipaasc63619.2025.10848671
Simulation to optimize the laboratory diagnosis of bacteremia.
Gerada, A., Roberts, G., Howard, A., Reza, N., Velluva, A., Rosato, C., . . . Hope, W. (2024). Simulation to optimize the laboratory diagnosis of bacteremia.. Microbiology spectrum, 12(11), e0144924. doi:10.1128/spectrum.01449-24
Enhanced SMC<sup>2</sup>: Leveraging Gradient Information from Differentiable Particle Filters Within Langevin Proposals
Rosato, C., Murphy, J., Varsi, A., Horridge, P., & Maskell, S. (2024). Enhanced SMC<sup>2</sup>: Leveraging Gradient Information from Differentiable Particle Filters Within Langevin Proposals. In 2024 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI) (pp. 1-8). IEEE. doi:10.1109/mfi62651.2024.10705779
Enhanced SMC$^2$: Leveraging Gradient Information from Differentiable Particle Filters Within Langevin Proposals
Bayesian Calibration to Address the Challenge of Antimicrobial Resistance: A Review
Rosato, C., Green, P. L., Harris, J., Maskell, S., Hope, W., Gerada, A., & Howard, A. (2024). Bayesian Calibration to Address the Challenge of Antimicrobial Resistance: A Review. IEEE Access, 12, 100772-100791. doi:10.1109/access.2024.3427410
2023
An O(log<sub>2</sub> N) SMC<sup>2</sup> Algorithm on Distributed Memory with an Approx. Optimal L-Kernel
Rosato, C., Varsi, A., Murphy, J., & Maskell, S. (2023). An O(log<sub>2</sub> N) SMC<sup>2</sup> Algorithm on Distributed Memory with an Approx. Optimal L-Kernel. In 2023 IEEE Symposium Sensor Data Fusion and International Conference on Multisensor Fusion and Integration (SDF-MFI) (pp. 1-8). IEEE. doi:10.1109/sdf-mfi59545.2023.10361452
Disease Surveillance using Bayesian Methods
Rosato, C. (2023, October 11). Disease Surveillance using Bayesian Methods.
Extracting Self-Reported COVID-19 Symptom Tweets and Twitter Movement Mobility Origin/Destination Matrices to Inform Disease Models
Rosato, C., Moore, R. E., Carter, M., Heap, J., Harris, J., Storopoli, J., & Maskell, S. (2023). Extracting Self-Reported COVID-19 Symptom Tweets and Twitter Movement Mobility Origin/Destination Matrices to Inform Disease Models. Information, 14(3), 170. doi:10.3390/info14030170
2022
Refining epidemiological forecasts with simple scoring rules
Moore, R. E., Rosato, C., & Maskell, S. (2022). Refining epidemiological forecasts with simple scoring rules. PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES, 380(2233). doi:10.1098/rsta.2021.0305
Inference of Stochastic Disease Transmission Models Using Particle-MCMC and a Gradient Based Proposal
Rosato, C., Harris, J., Panovska-Griffiths, J., & Maskell, S. (2022). Inference of Stochastic Disease Transmission Models Using Particle-MCMC and a Gradient Based Proposal. In 2022 25TH INTERNATIONAL CONFERENCE ON INFORMATION FUSION (FUSION 2022). Retrieved from https://www.webofscience.com/
Efficient Learning of the Parameters of Non-Linear Models using Differentiable Resampling in Particle Filters
Maskell, S., Devlin, L., Beraud, V., Horridge, P., & Rosato, C. (2022). Efficient Learning of the Parameters of Non-Linear Models using Differentiable Resampling in Particle Filters. IEEE Transactions on Signal Processing.