S. Acosta, An effective model of cerebrovascular pressure reactivity and blood flow autoregulation, Microvasc. Res, vol.115, pp.34-43, 2016.

J. Banus, Large Scale Cardiovascular Model Personalisation for Mechanistic Analysis of Heart and Brain Interactions, vol.3504, pp.285-293, 2019.
URL : https://hal.archives-ouvertes.fr/hal-02361466

P. Blanco, An anatomically detailed arterial network model for onedimensional computational hemodynamics, T-BME, vol.62, issue.2, pp.736-753, 2015.

M. Caruel, Dimensional reductions of a cardiac model for effective validation and calibration, Biomech. Model. Mechanobiol, vol.13, pp.897-914, 2014.
URL : https://hal.archives-ouvertes.fr/hal-00872746

S. R. Cox, Associations between vascular risk factors and brain MRI indices in UK Biobank, European Heart Journal, vol.44, pp.1-11, 2019.

W. Doehner, Heart and brain interaction in patients with heart failure: overview and proposal for a taxonomy, Europ. Jour. of H. Failure, vol.20, issue.2, 2018.

N. U. Epstein, K. A. Lane, M. R. Farlow, S. L. Risacher, A. J. Saykin et al., Cognitive dysfunction and greater visit-to-visit systolic blood pressure variability, Journal of the American Geriatrics Society, vol.61, issue.12, pp.2168-2173, 2013.

O. Ivanov, Variational autoencoder with arbitrary conditioning. 7th, ICLR, pp.1-25, 2019.

A. L. Jefferson, Lower Cardiac Output Is Associated with Greater White Matter Hyperintensities in Older Adults with Cardiovascular Disease, J Am Geriatr Soc, vol.55, pp.1044-1048, 2009.

A. Melis, Bayesian sensitivity analysis of a 1D vascular model with Gaussian process emulators, INT J NUMER METH BIO, vol.33, issue.12, pp.1-11, 2017.

R. Molléro, X. Pennec, H. Delingette, A. Garny, N. Ayache et al., Multifidelity-cma: a multifidelity approach for efficient personalisation of 3d cardiac electromechanical models, Biomechanics & Modeling in Mechanobiology, vol.17, issue.1, pp.285-300, 2017.

R. Molléro, Population-based priors in cardiac model personalisation for consistent parameter estimation in heterogeneous databases, INT J NUMER METH BIO, 2018.

L. O. Müller and E. F. Toro, Enhanced global mathematical model for studying cerebral venous blood flow, Journal of Biomechanics, vol.47, issue.13, pp.3361-3372, 2014.

P. Schmidt, Bayesian inference for structured additive regression models for largescale problems with applications to medical imaging, PhD, 2017.

J. M. Wardlaw, M. C. Valdés-hernández, and S. Muñoz-maniega, What are white matter hyperintensities made of? relevance to vascular cognitive impairment, Journal of the American Heart Association, vol.4, issue.6, 2015.