Stochastic (Mathematical modelling)

Girolami, M., Febrianto, E., Yin, G., & Cirak, F. The statistical finite element method (statFEM) for coherent synthesis of observation data and model predictions. arXiv:1905.06391.

J. T. Meech and P. Stanley-Marbell, "Efficient Programmable Random Variate Generation Accelerator from Sensor Noise," in IEEE Embedded Systems Letters, doi: 10.1109/LES.2020.3007005

Theoretical Population Biology (2020) 134: 61-76

Madge, Jim, Giovanni Colavizza, James Hetherington, Weisi Guo, and Alan Wilson. 2019. Assessing Simulations of Imperial Dynamics and Conflict in the Ancient World. Cliodynamics10:24–39.

Asymptotic Analysis of the LMS Algorithm with Momentum. Gerencsér, L.; Csáji, B. C.; Sabanis, S. 2018 . In: 57th IEEE Annual Conference on Decision and Control, CDC 2018. IEEE, pp. 3062-3067. ISBN 9781538613948

Aglietti, V., Damoulas, T. & Bonilla, E. (2019). Efficient Inference in Multi-task Cox Process Models. The 22nd International Conference on Artificial Intelligence and Statistics (AISTATS 2019).

On fixed gain recursive estimators with discontinuity in the parameters. Chau, H. N., Kumar, C., Rásonyi, M. & Sabanis, S. In : ESAIM: Probability and Statistics. 2019 ; Vol. 23. pp. 217-244

Angeli, Letizia; Grosskinsky, Stefan; Johansen, Adam M.; Pizzoferrato, Andrea. (2018). Rare event simulation for stochastic dynamics in continuous time. arXiv:1810.00693.

Paul Chleboun, Stefan Grosskinsky, Andrea Pizzoferrato, eprint arXiv:1804.07844: 04/2018.