Olivier Zahm

Research scientist at Inria

Short bio:

  • 2018-now: Research scientist (chargé de recherche) at Inria-Grenoble in the AIRSEA team.
  • 2015-2018: Postdoctoral associate at MIT in the UQGroup.
  • 2012-2015: Ph.D. at École Centrale Nantes.

 

(link to the group meeting

Publications

  1. Tiangang Cui, Xin Tong, Olivier Zahm : Prior normalization for certified likelihood-informed subspace detection of Bayesian inverse problems, preprint 2022. arXiv
  2. Tiangang Cui, Sergey Dolgov and Olivier Zahm: Conditional deep inverse Rosenblatt transports, preprint 2021. arXiv
  3. Daniele Bigoni, Youssef Marzouk, Clémentine Prieur, Olivier Zahm: Nonlinear dimension reduction for surrogate modeling using gradient information, preprint 2021. hal
  4. Tiangang Cui and Olivier Zahm: Data-free likelihood-informed dimension reduction of Bayesian inverse problems, Inverse Problem, 2021. link
  5. Ricardo Baptista, Youssef Marzouk, Rebecca Morrison, Olivier Zahm: Learning non-Gaussian graphical models via Hessian scores and triangular transport, preprint 2021. arXiv
  6. Jean Bernard Lasserre, Victor Magron, Swann Marx, Olivier Zahm: Minimizing rational functions: A hierarchy of approximations via pushforward measures, preprint 2020. arXiv
  7. Ricardo Baptista, Olivier Zahm and Youssef Marzouk: An adaptive transport framework for joint and conditional density estimation, preprint 2020. arXiv
  8. Michael Brennan, Daniele Bigoni, Olivier Zahm, Alessio Spantini, Youssef Marzouk: Greedy inference with structure-exploiting lazy maps, NeurIPS 2020. link
  9. Kathrin Smetana, Olivier Zahm: Randomized residual-based error estimators for the Proper Generalized Decomposition approximation of parametrized problems, IJNME 2019. arXiv
  10. Rémi Lam, Olivier Zahm, Youssef Marzouk and Karen Willcox: Multifidelity Dimension Reduction via Active Subspaces, SIAM-SISC, 42(2) 2020. arXiv.
  11. Kathrin Smetana, Olivier Zahm and Anthony T. Patera: Randomized residual-based error estimators for parametrized equations, SIAM-SISC, 41(2), p. A900–A926, 2019. link, arXiv.
  12. Olivier Zahm, Tiangang Cui, Kody Law, Alessio Spantini and Youssef Marzouk: Certified dimension reduction in nonlinear Bayesian inverse problems, preprint 2018. arXiv
  13. Olivier Zahm, Paul Constantine, Clémentine Prieur and Youssef Marzouk: Gradient-based dimension reduction of multivariate vector-valued functions, SIAM-SISC 42(1). arXiv.
  14. Weiqi Ji, Jiaxing Wang, Olivier Zahm, Youssef Marzouk, Bin Yang, Zhuyin Ren and Chung K. Law: Shared low-dimensional subspaces for propagating kinetic uncertainty to multiple outputs, Combustion and Flame, Volume 190, p. 146-157, 2017. link.
  15. Olivier Zahm, Marie Billaud-Friess and Anthony Nouy: Projection based model order reduction methods for the estimation of vector-valued variables of interest, SIAM-SISC 39(4), p. A1647-A1674, 2015. link, arXiv.
  16. Olivier Zahm and Anthony Nouy: Interpolation of inverse operators for preconditioning parameter-dependent equations, SIAM-SISC, 38(2), p. A1044-A107, 2016. link, arXiv.
  17. Paul Cazeaux and Olivier Zahm: A fast boundary element method for the solution of periodic many-inclusion problems via hierarchical matrix techniques, ESAIM:Proc, Vol. 48, p. 156-168, 2015. link.
  18. Marie Billaud-Friess, Anthony Nouy and Olivier Zahm: A tensor approximation method based on ideal minimal residual formulations for the solution of high-dimensional problems, ESAIM: M2AN 48, p. 1777-1806, 2014. link, arXiv.

PhD thesis (supervisor: Anthony Nouy and Marie Billaud-Freiss):

Model order reduction methods for parameter-dependent equations: Applications in Uncertainty Quantification, 2015. link.

 

 

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