2022

Borowska, A. and King, R. (2022) Semi-complete data augmentation for efficient state space model fitting. Journal of Computational and Graphical Statistics, (doi: 10.1080/10618600.2022.2077350) (Early Online Publication)

Borowska, A. , Gao, H. , Lazarus, A. and Husmeier, D. (2022) Bayesian optimisation for efficient parameter inference in a cardiac mechanics model of the left ventricle. International Journal for Numerical Methods in Biomedical Engineering, 38(5), e3593. (doi: 10.1002/cnm.3593) (PMID:35302293)

2021

Romaszko, L., Borowska, A. , Lazarus, A., Dalton, D., Berry, C. , Luo, X. , Husmeier, D. and Gao, H. (2021) Neural network-based left ventricle geometry prediction from CMR images with application in biomechanics. Artificial Intelligence In Medicine, 119, 102140. (doi: 10.1016/j.artmed.2021.102140)

Paun, L. M., Borowska, A. , Colebank, M. J., Olufsen, M. S. and Husmeier, D. (2021) Inference in Cardiovascular Modelling Subject to Medical Interventions. In: 3rd International Conference on Statistics: Theory and Applications (ICSTA'21), 29-31 Jul 2021, p. 109. ISBN 9781927877913 (doi: 10.11159/icsta21.109)

Borowska, A. , Giurghita, D. and Husmeier, D. (2021) Gaussian process enhanced semi-automatic approximate Bayesian computation: parameter inference in a stochastic differential equation system for chemotaxis. Journal of Computational Physics, 429, 109999. (doi: 10.1016/j.jcp.2020.109999)

2020

Borowska, A. , Hoogerheide, L., Koopman, S. J. and van Dijk, H. K. (2020) Partially censored posterior for robust and efficient risk evaluation. Journal of Econometrics, 217(2), pp. 335-355. (doi: 10.1016/j.jeconom.2019.12.007)

2019

Husmeier, D. , Lazarus, A., Noè, U. , Davies, V. , Borowska, A. , Macdonald, B. , Gao, H. , Berry, C. and Luo, X. (2019) Statistical Emulation of Cardiac Mechanics: an Important Step Towards a Clinical Decision Support System. In: International Conference on Statistics: Theory and Applications (ICSTA’19), Lisbon, Portugal, 13-14 Aug 2019, p. 29. ISBN 9781927877647 (doi: 10.11159/icsta19.29)

Romaszko, L., Borowska, A. , Lazarus, A., Gao, H. , Luo, X. and Husmeier, D. (2019) Direct Learning Left Ventricular Meshes from CMR Images. In: International Conference on Statistics: Theory and Applications (ICSTA’19), Lisbon, Portugal, 13-14 Aug 2019, p. 25. ISBN 9781927877647 (doi: 10.11159/icsta19.25)

Romaszko, L., Lazarus, A., Gao, H. , Borowska, A. , Luo, X. and Husmeier, D. (2019) Massive Dimensionality Reduction for the Left Ventricular Mesh. In: International Conference on Statistics: Theory and Applications (ICSTA’19), Lisbon, Portugal, 13-14 Aug 2019, p. 24. ISBN 9781927877647 (doi: 10.11159/icsta19.24)

Baştürk, N., Borowska, A. , Grassi, S., Hoogerheide, L. and van Dijk, H.K. (2019) Forecast density combinations of dynamic models and data driven portfolio strategies. Journal of Econometrics, 210, pp. 170-186. (doi: 10.1016/j.jeconom.2018.11.011)

Borowska, A. , Hoogerheide, L. F. and Koopman, S. J. (2019) Bayesian Risk Forecasting for Long Horizons. Discussion Paper. Tinbergen Institute. (doi: 10.2139/ssrn.3339819).

2018

Barra, I., Borowska, A. and Koopman, S. J. (2018) Bayesian dynamic modeling of high-frequency integer price changes. Journal of Financial Econometrics, 16(3), pp. 384-424. (doi: 10.1093/jjfinec/nby010)

Articles

Borowska, A. and King, R. (2022) Semi-complete data augmentation for efficient state space model fitting. Journal of Computational and Graphical Statistics, (doi: 10.1080/10618600.2022.2077350) (Early Online Publication)

Borowska, A. , Gao, H. , Lazarus, A. and Husmeier, D. (2022) Bayesian optimisation for efficient parameter inference in a cardiac mechanics model of the left ventricle. International Journal for Numerical Methods in Biomedical Engineering, 38(5), e3593. (doi: 10.1002/cnm.3593) (PMID:35302293)

Romaszko, L., Borowska, A. , Lazarus, A., Dalton, D., Berry, C. , Luo, X. , Husmeier, D. and Gao, H. (2021) Neural network-based left ventricle geometry prediction from CMR images with application in biomechanics. Artificial Intelligence In Medicine, 119, 102140. (doi: 10.1016/j.artmed.2021.102140)

Borowska, A. , Giurghita, D. and Husmeier, D. (2021) Gaussian process enhanced semi-automatic approximate Bayesian computation: parameter inference in a stochastic differential equation system for chemotaxis. Journal of Computational Physics, 429, 109999. (doi: 10.1016/j.jcp.2020.109999)

Borowska, A. , Hoogerheide, L., Koopman, S. J. and van Dijk, H. K. (2020) Partially censored posterior for robust and efficient risk evaluation. Journal of Econometrics, 217(2), pp. 335-355. (doi: 10.1016/j.jeconom.2019.12.007)

Baştürk, N., Borowska, A. , Grassi, S., Hoogerheide, L. and van Dijk, H.K. (2019) Forecast density combinations of dynamic models and data driven portfolio strategies. Journal of Econometrics, 210, pp. 170-186. (doi: 10.1016/j.jeconom.2018.11.011)

Barra, I., Borowska, A. and Koopman, S. J. (2018) Bayesian dynamic modeling of high-frequency integer price changes. Journal of Financial Econometrics, 16(3), pp. 384-424. (doi: 10.1093/jjfinec/nby010)

Research Reports or Papers

Borowska, A. , Hoogerheide, L. F. and Koopman, S. J. (2019) Bayesian Risk Forecasting for Long Horizons. Discussion Paper. Tinbergen Institute. (doi: 10.2139/ssrn.3339819).

Conference Proceedings

Paun, L. M., Borowska, A. , Colebank, M. J., Olufsen, M. S. and Husmeier, D. (2021) Inference in Cardiovascular Modelling Subject to Medical Interventions. In: 3rd International Conference on Statistics: Theory and Applications (ICSTA'21), 29-31 Jul 2021, p. 109. ISBN 9781927877913 (doi: 10.11159/icsta21.109)

Husmeier, D. , Lazarus, A., Noè, U. , Davies, V. , Borowska, A. , Macdonald, B. , Gao, H. , Berry, C. and Luo, X. (2019) Statistical Emulation of Cardiac Mechanics: an Important Step Towards a Clinical Decision Support System. In: International Conference on Statistics: Theory and Applications (ICSTA’19), Lisbon, Portugal, 13-14 Aug 2019, p. 29. ISBN 9781927877647 (doi: 10.11159/icsta19.29)

Romaszko, L., Borowska, A. , Lazarus, A., Gao, H. , Luo, X. and Husmeier, D. (2019) Direct Learning Left Ventricular Meshes from CMR Images. In: International Conference on Statistics: Theory and Applications (ICSTA’19), Lisbon, Portugal, 13-14 Aug 2019, p. 25. ISBN 9781927877647 (doi: 10.11159/icsta19.25)

Romaszko, L., Lazarus, A., Gao, H. , Borowska, A. , Luo, X. and Husmeier, D. (2019) Massive Dimensionality Reduction for the Left Ventricular Mesh. In: International Conference on Statistics: Theory and Applications (ICSTA’19), Lisbon, Portugal, 13-14 Aug 2019, p. 24. ISBN 9781927877647 (doi: 10.11159/icsta19.24)