Carlos A.C.C. Perello

Carlos A.C.C. Perello

Mathematics student

Publications

Graph-based mutually exciting point processes for modelling event times in docked bike-sharing systems

Preprint (submitted for publication), 2023

This paper is an extension of my 2nd year group project, which consisted on fitting Hawkes processes to the London Santander Cycle bike-sharing system. In this paper we employ a spatial component in the model to take in account distances between docking stations when predicting bike usage.

Recommended citation: F. Sanna Passino, Y. Che, C. C. Perello, C. A. (2023). Graph-based mutually exciting point processes for modelling event times in docked bike-sharing systems. https://arxiv.org/abs/2311.00595

Adaptively Optimised Adaptive Importance Samplers

Preprint (submitted for publication), 2023

This paper, which stemmed out of my BSc project, introduces a new adaptive importance sampling algorithm that used adaptive optimisation to adapt the proposal distribution.

Recommended citation: C. C. Perello, C. A., Akyildiz, Ö. D. (2023). Adaptively Optimised Adaptive Importance Samplers. https://arxiv.org/abs/2307.09341

Regularised B-splines projected Gaussian Process priors to estimate time-trends of age-specific COVID-19 deaths related to vaccine roll-out

Appeared in Bayesian Analysis on Sep 2023, 2021

In this paper we fit beta splines to COVID-19 mortality data for each US state and use the fitted curves to estimate future deaths.

Recommended citation: Monod, M., Blenkinsop, A., Brizzi, A., Chen, Y., Perello, C. C. C., Jogarah, V., Wang, Y., Flaxman, S., Bhatt, S., & Ratmann, O. (2021). Regularised B-splines projected Gaussian Process priors to estimate time-trends of age-specific COVID-19 deaths related to vaccine roll-out. https://arxiv.org/abs/2106.12360