Machine learning techniques
(with C. Huré, A. Bachouch, N. Langrené)
SIAM Journal on Numerical Analysis, 2021, 59(1), 525-557.
Deep neural networks algorithms for stochastic control problems on finite horizon: numerical applications
(with A. Bachouch, C. Huré, N. Langrené)
Methodology and Computing in Applied Probability, 2022, Vol 24, pp 143-178.
(formerly entitled: Some machine learning schemes for high-dimensional nonlinear PDEs), (with C. Huré, X. Warin)
Mathematics of Computation, 2020, vol 89(324), pp. 1547-1580
Neural networks-based backward scheme for fully nonlinear PDEs (with M. Germain, X. Warin)
SN Partial Differential Equations and Applications, 2021, Vol 2(1), article 16.
Approximation error analysis of some deep backward schemes for nonlinear PDEs (with M. Germain, X. Warin)
SIAM Journal of Scientific Computing, 2022, Vol 44(1), A28-A56
DeepSets and their derivative networks for solving symmetric PDEs (with M. Germain, M. Laurière, X. Warin)
Journal of Scientific Computing, 2022, Vol 91, article 63, https://doi.org/10.1007/s10915-022-01796-w
Neural networks-based algorithms for stochastic control and PDEs in finance (with M. Germain, X. Warin)
Machine Learning for Financial Markets: a guide to contemporary practices, 2023, Cambridge University Press, Editors: Agostino Capponi and Charles-Albert Lehalle,
Rate of convergence for particles approximation of PDEs in Wasserstein space (with M. Germain, X. Warin)
Journal of Applied Probability, 2022, vol 59(4), 992-1008
Differential learning methods for solving fully nonlinear PDEs (with W. Lefebvre, G. Loeper)
Digital Finance, 2023, vol 5, 183-229,
Numerical methods and quantization