[1] F. Bachoc, A. Bachouch and L. Lenôtre. Hastings-Metropolis algorithm on Markov chains for small-
probability estimation. ESAIM Proceedings and Surveys 48, 276-307, 2015.
Journal link: http://www.esaimproc.org/articles/proc/abs/2015/01/proc144813/proc144813.html
Available on Hal
[2] A. Bachouch, M. A. Ben Lasmer, A. Matoussi and M. Mnif. Euler time discretization of Backward Doubly SDEs and application to Semilinear SPDEs. Stochastics and Partial Differential Equations: Analysis and Computations, 2016.
Journal link: http://link.springer.com/article/10.1007/s40072-016-0071-4 .
Available on arXiv
[3] A. Bachouch , E. Gobet and A. Matoussi. Empirical Regression Method for Backward doubly stochastic differentialequations. SIAM/ASA J. Uncertainty Quantification, 4(1), 358-379, 2016.
Journal link: http://epubs.siam.org/doi/abs/10.1137/15M1022094
Available on Hal.
[4] N. Agram, A. Bachouch, B. Øksendal and F. Proske. Singular control and optimal stopping of memory mean-field processes. SIAM Journal on Mathematical Analysis, 51(1), 450-468, 2019.
Link: https://epubs.siam.org/doi/abs/10.1137/18M1174787
https://doi.org/10.1137/18M1174787
Available on arXiv: https://arxiv.org/pdf/1802.05527.pdf
[5] A. Bachouch and A. Matoussi. Zhang L2-Regularity for the solutions of Backward Doubly Stochastic Differential Equations under globally Lipschitz continuous assumptions. Stochastics and Dynamics, 20(2), 2020.
Link: https://www.worldscientific.com/doi/abs/10.1142/S0219493720500124
https://doi.org/10.1142/S0219493720500124
Available on arXiv : https://arxiv.org/pdf/1709.07627.pdf
[6] C. Huré, H. Pham, A. Bachouch & N. Langrené. Deep neural networks algorithms for stochastic control problems on finite horizon, part I: convergence analysis. SIAM Journal on Numerical Analysis, 59(1), 525-557, 2021.
Link: https://epubs.siam.org/toc/sjnaam/59/1
DOI: 10.1137/20M1316640
Available on arXiv: https://arxiv.org/pdf/1812.04300.pdf
[7] A. Bachouch, C. Huré, N. Langrené & H. Pham. Deep neural networks algorithms for stochastic control problems on finite horizon, part 2: Numerical applications. Methodology and Computing in Applied Probability, 24, 143 – 178, 2022.
Link: https://link.springer.com/article/10.1007/s11009-019-09767-9
DOI: 10.1007/s11009-019-09767-9
Available on arXiv: https://arxiv.org/pdf/1812.05916.pdf
Preprints:
[8] A. Bachouch, B. Øksendal & O. Draouil. A new approach to optimal stopping for Hunt processes. Preprint, 2022.
Available on arXiv.
[9] A. Bachouch , E. Gobet and A. Matoussi. Numerical Computations for Quasilinear Stochastic PDEs. Preprint, 2022. Available upon request.
PhD thesis
[10] Numerical Computations for Backward Doubly Stochastic Differential Equations and Non-linear Stochastic PDEs (October 2014). (pdf). TEL version.
Co-authors: