Vincent Duval is an INRIA researcher in the MOKAPLAN team. After completing his engineering studies in applied mathematics at Ecole polytechnique and Télécom ParisTech, he obtained a PhD degree in 20011 at Télécom ParisTech for his thesis on denoising methods in imaging. Then, he worked for almost two years at the ANSSI as an engineer. In 2013, he joined Gabriel Peyré's team for a postdoc in CEREMADE. In 2014, he obtained a position as an INRIA researcher (détaché du corps des Mines) in the MOKAPLAN team. He obtained the "habilitation à diriger des recherches" in 2022. His research interests include variational problems in the space of measures, with applications in image processing or physics.
Duval V. (2021), An Epigraphical Approach to the Representer Theorem, Journal of Convex Analysis, vol. 28, n°3, p. 819-836
Bleyer J., Carlier G., Duval V., Mirebeau J-M., Peyré G. (2016), A Γ-Convergence Result for the Upper Bound Limit Analysis of Plates, ESAIM: Mathematical Modelling and Numerical Analysis, vol. 50, n°1, p. 215-235
De Castro Y., Duval V., Petit R. (2021), Towards Off-the-grid Algorithms for Total Variation Regularized Inverse Problems, in Abderrahim Elmoataz, Jalal Fadili, Yvain Quéau, Julien Rabin, Loïc Simon, Scale Space and Variational Methods in Computer Vision, Proceedings of SSVM 2021, 553-564 p.
Duval V., Peyré G. (2015), The Non Degenerate Source Condition: Support Robustness for Discrete and Continuous Sparse Deconvolution, in , IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, Dec 2015, Cancun, Mexico, Cancun, IEEE - Institute of Electrical and Electronics Engineers
Tovey R., Duval V. (2022), Dynamical Programming for off-the-grid dynamic Inverse Problems, Paris, Cahier de recherche CEREMADE, Université Paris Dauphine-PSL, 43 p.
De Castro Y., Duval V., Petit R. (2021), Towards Off-the-grid Algorithms for Total Variation Regularized Inverse Problems, Paris, Cahier de recherche CEREMADE, Université Paris Dauphine-PSL, 25 p.
Duval V., Peyré G. (2015), Sparse Spikes Deconvolution on Thin Grids, Paris, Université Paris-Dauphine, 56 p.
Duval V. (2014), A comparative analysis of the TVL1 and the TV-G models, Université Paris-Dauphine, 26 p.