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Publications

Selected publications

  1. Simulation to optimize the laboratory diagnosis of bacteremia. (Journal article - 2024)
  2. Bayesian Calibration to Address the Challenge of Antimicrobial Resistance: A Review (Journal article - 2024)
  3. Refining epidemiological forecasts with simple scoring rules (Journal article - 2022)
  4. Enhanced SMC<sup>2</sup>: Leveraging Gradient Information from Differentiable Particle Filters Within Langevin Proposals (Conference Paper - 2024)
  5. An O(log<sub>2</sub> N) SMC<sup>2</sup> Algorithm on Distributed Memory with an Approx. Optimal L-Kernel (Conference Paper - 2023)
  6. Inference of Stochastic Disease Transmission Models Using Particle-MCMC and a Gradient Based Proposal (Conference Paper - 2022)
  7. Efficient Learning of the Parameters of Non-Linear Models using Differentiable Resampling in Particle Filters (Journal article - 2022)
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2024

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

DOI
10.1109/mfi62651.2024.10705779
Conference Paper

Enhanced SMC$^2$: Leveraging Gradient Information from Differentiable Particle Filters Within Langevin Proposals

DOI
10.48550/arxiv.2407.17296
Preprint

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

DOI
10.1109/sdf-mfi59545.2023.10361452
Conference Paper

2022

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/

Conference Paper

Inference of Stochastic Disease Transmission Models Using Particle-MCMC and a Gradient Based Proposal

DOI
10.48550/arxiv.2205.07356
Preprint

2021

Fusing Low-Latency Data Feeds with Death Data to Accurately Nowcast COVID-19 Related Deaths

DOI
10.48550/arxiv.2112.08097
Preprint

Efficient Learning of the Parameters of Non-Linear Models using Differentiable Resampling in Particle Filters.

Preprint