Inverse Problems: A Deterministic Approach using Physics-Based Reduced Models [Lecture Notes].
O. Mula. 2022. [pdf]
 Deep Learning-Based schemes for Singularly Perturbed Convection-Diffusion Problems.
A. Beguinet, V. Ehrlacher, R. Flenghi, M. Fuente, O. Mula and A. Somacal. 2022. [pdf]
 Wasserstein Model Reduction Approach for Parametrized Flow Problems in Porous Media.
B. Battisti, T. Blickham, G. Enchery, V. Ehrlacher, D. Lombardi and O. Mula. 2022. [pdf]
 Impact of Physical Model Error on State Estimation for Neutronics Applications.
Y. Conjungo, D. Labeurthre, F. Madiot, O. Mula and T. Taddei. 2022. [pdf]
[A1] State Estimation with Model Reduction and Shape Variability. Application to biomedical problems.
F. Galarce, D. Lombardi and O. Mula. SIAM J. Scientific Computing (in print). 2022. [pdf]
[A4] Fast reconstruction of 3D blood flows from Doppler ultrasound images and reduced models.
F. Galarce, J.F. Gerbeau, D. Lombardi and O. Mula. Computer Methods in Applied Mechanics and Engineering. 2021. [pdf, doi]
[A8] Nonlinear model reduction on metric spaces. Application to one-dimensional conservative PDEs in Wasserstein spaces.
V. Ehrlacher, D. Lombardi, O. Mula and F.-X. Vialard. ESAIM M2AN. 2020. [pdf, doi, code]
[A11] Greedy algorithms for optimal measurements selection in state estimation using reduced models.
P. Binev, A. Cohen, O. Mula and J. Nichols. SIAM Journal on Uncertainty Quantification. 2018. [pdf, doi]
[A12] Sensor placement in nuclear reactors based on the Generalized Empirical Interpolation Method.
J.-P. Argaud, B. Bouriquet, F. de Caso, H. Gong, Y. Maday and O. Mula. Journal of Computational Physics. 2018. [pdf, doi]
[A15] The Generalized Empirical Interpolation Method: Stability theory on Hilbert spaces with an application to the Stokes equation.
Y. Maday, O. Mula, A.T. Patera and M. Yano. Computer Methods in Applied Mechanics and Engineering. 2015. [pdf, doi]
[A16] A Generalized Empirical Interpolation Method: application of reduced basis techniques to data assimilation.
Y. Maday and O. Mula. Analysis and Numerics of Partial Differential Equations. 2013. [pdf, doi]
[P1] Stabilization of (G)EIM in Presence of Measurement Noise: Application to Nuclear Reactor Physics.
J. P. Argaud, B. Bouriquet, H. Gong, Y. Maday and O. Mula.
In Spectral and High Order Methods for Partial Differential Equations ICOSAHOM 2016. 2017. [pdf, doi]
[P2] The parareal in time algorithm applied to the kinetic neutron diffusion equation.
A.-M. Baudron, J.J. Lautard, Y. Maday and O. Mula.
In Domain Decomposition Methods in Science and Engineering XXI. 2014. [pdf, doi]
[P3] MINARET: Towards a time-dependent neutron transport parallel solver.
A.M. Baudron, J.J. Lautard, Y. Maday and O. Mula.
In SNA+ MC 2013-Joint International Conference on Supercomputing in Nuclear Applications+ Monte Carlo. 2014. [pdf, doi]
[P5] A new methodology for enhanced natural safety GEN-IV SFR core design: application to a carbide-fueled core.
N.E. Stauff, M. Agard, L. Buiron, B. Fontaine, X. Jeanningros, O. Mula, G. Rimpault and M. Zabiego.
In Proceedings of ICAPP 2011. 2011. [pdf]
 Report 2: Impact of mobility and population density on the Covid-19 outbreak (February-Nov 2020).
J. Atif, B. Cabot, O. Cappé, O. Mula and Pinot. R.. 2020. [pdf]
 Report 1: Feedback on mobility during the Covid-19 epidemic (February-May 2020).
J. Atif, O. Cappé, A. Kazakci, Y. Léo, L. Massoulié and O. Mula. 2020. [pdf]
[T1] [Habilitation Thesis] Linear and Nonlinear Schemes for Forward and Inverse Problems.
O. Mula. 2021. [pdf]
[T2] [PhD Thesis] Some contributions towards the parallel simulation of time dependent neutron transport and the integration of observed data in real time..
O. Mula. 2014. [pdf]
 PBDW method for state estimation: error analysis for noisy data and nonlinear formulation.
H. Gong, Y. Maday, O. Mula and T. Taddei. 2019. [pdf]