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Bibliography

Publications of the year

Articles in International Peer-Reviewed Journals

  • 1E. Blayo, D. Cherel, A. Rousseau.

    Towards optimized Schwarz methods for the Navier-Stokes equations, in: Journal of Scientific Computing, 2015, 22 p.

    https://hal.inria.fr/hal-00982087
  • 2E. Blayo, A. Rousseau.

    About Interface Conditions for Coupling Hydrostatic and Nonhydrostatic Navier-Stokes Flows, in: Discrete and Continuous Dynamical Systems - Series S, 2015, 10 p.

    https://hal.inria.fr/hal-01185255
  • 3T. Capelle, P. Sturm, A. Vidard.

    Formulating LUTI Calibration as an Optimisation Problem: Example of Tranus Shadow Price Estimation, in: Procedia Engineering, 2015, vol. 115, pp. 12-20. [ DOI : 10.1016/j.proeng.2015.07.349 ]

    https://hal.inria.fr/hal-01237639
  • 4V. Chabot, M. Nodet, N. Papadakis, A. Vidard.

    Accounting for observation errors in image data assimilation, in: Tellus A, February 2015, vol. 67, no 23629, 19 p. [ DOI : 10.3402/tellusa.v67.23629 ]

    https://hal.inria.fr/hal-00923735
  • 5L. Debreu, E. Neveu, E. Simon, F.-X. Le Dimet, A. Vidard.

    Multigrid solvers and multigrid preconditioners for the solution of variational data assimilation problems, in: Quarterly Journal of the Royal Meteorological Society, September 2015. [ DOI : 10.1002/qj.2676 ]

    https://hal.inria.fr/hal-01246349
  • 6L. Gilquin, C. Prieur, E. Arnaud.

    Replication procedure for grouped Sobol' indices estimation in dependent uncertainty spaces, in: Information and Inference, August 2015, vol. 4, no 4, pp. 354-379. [ DOI : 10.1093/imaiai/iav010 ]

    https://hal.inria.fr/hal-01045034
  • 7A. Janon, M. Nodet, C. Prieur.

    Goal-oriented error estimation for the reduced basis method, with application to sensitivity analysis, in: Journal of Scientific Computing, November 2015.

    https://hal.archives-ouvertes.fr/hal-00721616
  • 8A. Janon, M. Nodet, C. Prieur, C. Prieur.

    Global sensitivity analysis for the boundary control of an open channel, in: Mathematics of Control, Signals, and Systems, 2016, vol. 28, no 1.

    https://hal.archives-ouvertes.fr/hal-01065886
  • 9E. Kazantsev.

    Optimized boundary conditions at staircase-shaped coastlines, in: Ocean Dynamics, January 2015, vol. 65, no 1, pp. 49-63. [ DOI : 10.1007/s10236-014-0780-z ]

    https://hal.inria.fr/hal-00952847
  • 10C. Kazantsev, E. Kazantsev, M. Tolstykh.

    Variational Data Assimilation for Optimizing Boundary Conditions in Ocean Models, in: Meteorologiya i Gidrologiya / Russian Meteorology and Hydrology, June 2015, vol. 40, no 6, pp. 383-391. [ DOI : 10.3103/S1068373915060047 ]

    https://hal.inria.fr/hal-01251353
  • 11F.-X. Le Dimet, I. Souopgui, O. Titaud, V. Shutyaev, M. Y. Hussaini.

    Toward the assimilation of images, in: Nonlinear Processes in Geophysics, 2015, vol. 22, pp. 15-32. [ DOI : 10.5194/npg-22-15-2015 ]

    https://hal.inria.fr/hal-01103151
  • 12F. Lemarié, E. Blayo, L. Debreu.

    Analysis of ocean-atmosphere coupling algorithms : consistency and stability, in: Procedia Computer Science, 2015, vol. 51, pp. 2066–2075. [ DOI : 10.1016/j.procs.2015.05.473 ]

    https://hal.inria.fr/hal-01174132
  • 13F. Lemarié, L. Debreu, G. Madec, J. Demange, J.-M. Molines, M. Honnorat.

    Stability constraints for oceanic numerical models: implications for the formulation of time and space discretizations, in: Ocean Modelling, 2015, vol. 92, pp. 124–148. [ DOI : 10.1016/j.ocemod.2015.06.006 ]

    https://hal.inria.fr/hal-01065979
  • 14V. Oerder, F. Colas, V. Echevin, S. Masson, C. Hourdin, S. Jullien, G. Madec, F. Lemarié.

    Mesoscale SST–wind stress coupling in the Peru–Chile current system: Which mechanisms drive its seasonal variability?, in: Climate Dynamics, January 2016. [ DOI : 10.1007/s00382-015-2965-7 ]

    https://hal.inria.fr/hal-01253181
  • 15V. P. Shutyaev, F.-X. Le Dimet, V. I. Agoshkov, E. I. Parmuzin.

    Sensitivity of Functionals in Problems of Variational Assimilation of Observational Data, in: Izvestiya Atmospheric and Oceanic Physics / Izvestiya Rossiiskoi Akademii Nauk Fizika Atmosfery i Okeana, March 2015, vol. 51, no 3, pp. 349-357. [ DOI : 10.1134/S0001433815030111 ]

    https://hal.inria.fr/hal-01252779
  • 16Y. Soufflet, P. Marchesiello, F. Lemarié, J. Jouanno, X. Capet, L. Debreu, R. Benshila.

    On effective resolution in ocean models, in: Ocean Modelling, December 2015. [ DOI : 10.1016/j.ocemod.2015.12.004 ]

    https://hal.inria.fr/hal-01250231
  • 17I. Souopgui, H. E. Ngodock, A. Vidard, F.-X. Le Dimet.

    Incremental projection approach of regularization for inverse problems, in: Applied Mathematics & Optimization, September 2015, 22 p. [ DOI : 10.1007/s00245-015-9315-3 ]

    https://hal.inria.fr/hal-01205235
  • 18P. Tencaliec, A.-C. Favre, C. Prieur, T. Mathevet.

    Reconstruction of missing daily streamflow data using dynamic regression models, in: Water Resources Research, 2016.

    https://hal.inria.fr/hal-01245238
  • 19A. Vidard, P.-A. Bouttier, F. Vigilant.

    NEMOTAM: tangent and adjoint models for the ocean modelling platform NEMO, in: Geoscientific Model Development, April 2015, vol. 8, pp. 1245-1257. [ DOI : 10.5194/gmd-8-1245-2015 ]

    https://hal-insu.archives-ouvertes.fr/insu-01164710

Invited Conferences

  • 20N. Feyeux, A. Vidard, M. Nodet.

    Optimal transport for data assimilation, in: Workshop transport optimal : théorie et applications, Bordeaux, France, October 2015.

    https://hal.inria.fr/hal-01251809

International Conferences with Proceedings

  • 21A. Vidard, M. Nodet, V. Chabot.

    Dealing whith occultation when accounting for observation error correlation in a wavelet space, in: Multitemp 2015, Annecy, France, July 2015.

    https://hal.inria.fr/hal-01251711

Conferences without Proceedings

  • 22P.-A. Bouttier, J.-M. Brankart, G. Candille, A. Vidard, E. Blayo, J. Verron, P. Brasseur.

    Toward variational assimilation of SARAL/Altika altimeter data in a North Atlantic circulation model at eddy-permitting resolution: assessment of a NEMO-based 4D-VAR system, in: European Geophysical Union General Assembly 2015, Vienna, Austria, April 2015.

    https://hal.inria.fr/hal-01250601
  • 23T. Capelle, P. Sturm, A. Vidard, B. Morton.

    Contributions to the calibration of integrated land use and transportation models, in: 14th International Conference on Computers in Urban Planning and Urban Management, Boston, United States, July 2015.

    https://hal.inria.fr/hal-01237628
  • 24T. Capelle, P. Sturm, A. Vidard, B. Morton.

    Formulating LUTI Calibration As an Optimisation Problem: Estimation of Tranus Shadow Price and Substitution Parameters, in: AAAI-15 Workshop on Computational Sustainability, Austin, Texas, United States, January 2015.

    https://hal.inria.fr/hal-01237622
  • 25G. Dollé, O. Duran, N. Feyeux, E. Frénod, M. Giacomini.

    SiViBiR++ project: Simulation of a Virtual Bioreactor Landfill using Feel++, in: CEMRACS 2015, Luminy, France, July 2015.

    https://hal.archives-ouvertes.fr/hal-01222253
  • 26F. Lemarié, L. Debreu.

    Improving vertical advection in oceanic modeling, in: Partial Differential Equations on the Sphere Workshop, Seoul, South Korea, KOREA Institute of Atmospheric Prediction Systems (KIAPS), October 2015.

    https://hal.inria.fr/hal-01250645
  • 27M. Nodet.

    Goal-oriented error estimation for the reduced basis method, in: Model Reduction of Parametrized Systems III MoRePaS 2015, Trieste, Italy, October 2015.

    https://hal.inria.fr/hal-01251743
  • 28A. Vidard, V. Chabot, M. Nodet.

    Wavelet based representation of observation error covariance, in: 1st GODAE OceanView Data Assimilation Task Team (DA-TT) Workshop, Exeter, United Kingdom, May 2015.

    https://hal.inria.fr/hal-01251665
  • 29A. Vidard.

    Global 1° 4D-var ocean reanalysis, is it worth the pain?, in: 1st GODAE OceanView Data Assimilation Task Team (DA-TT) Workshop, Exeter, United Kingdom, May 2015.

    https://hal.inria.fr/hal-01251659

Internal Reports

  • 30F. Lemarié.

    Numerical modification of atmospheric models to include the feedback of oceanic currents on air-sea fluxes in ocean-atmosphere coupled models, Inria Grenoble - Rhône-Alpes ; Laboratoire Jean Kuntzmann ; Universite de Grenoble I - Joseph Fourier ; Inria, August 2015, no RT-0464.

    https://hal.inria.fr/hal-01184711

Scientific Popularization

Other Publications

  • 34C. Kazantsev, E. Kazantsev.

    Optimizing Lateral Boundary Conditions at Staircase-shaped Coastlines: Variational Approach, June 2015, Modern Problems in Numerical Mathematics and Mathematical Modeling.

    https://hal.inria.fr/hal-01252825
  • 35A. Makris, C. Prieur, T. Vischel, G. Quantin, T. Lebel, R. Roca.

    Stochastic Tracking of Mesoscale Convective Systems: Evaluation in the West AfricanSahel, August 2015, To appear in Stochastic Environmental Research and Risk Assessment. [ DOI : 10.1007/s00477-015-1102-9 ]

    https://hal.archives-ouvertes.fr/hal-01187153
  • 36S. Nanty, C. Helbert, A. Marrel, N. Pérot, C. Prieur.

    Sampling, metamodelling and sensitivity analysis of numerical simulators with functional stochastic inputs, 2015, working paper or preprint.

    https://hal.archives-ouvertes.fr/hal-01187162
  • 37M. Nodet, A. Vidard.

    Variational methods, June 2015, working paper or preprint.

    https://hal.inria.fr/hal-01251720
References in notes
  • 38D. Auroux, J. Fehrenbach.

    Identification of velocity fields for geophysical fluids from a sequence of images, in: Exp. Fluids, 2010.

    http://dx.doi.org/10.1007/s00348-010-0926-9
  • 39F. Caron, P. Del Moral, A. Doucet, M. Pace.

    Particle approximation of the intensity measures of a spatial branching point process arising in multitarget tracking, in: SIAM J. Control Optim., 2011, vol. 49, no 4, pp. 1766–1792.

    http://dx.doi.org/10.1137/100788987
  • 40P. Cattiaux, J. R. Leon, C. Prieur.

    Estimation for Stochastic Damping Hamiltonian Systems under Partial Observation. I. Invariant density., in: Stochastic Processes and their Applications, March 2014, vol. 124, no 3, pp. 1236-1260. [ DOI : 10.1016/j.spa.2013.10.008 ]

    https://hal.archives-ouvertes.fr/hal-00739136
  • 41P. Cattiaux, J. R. Leon, C. Prieur.

    Estimation for Stochastic Damping Hamiltonian Systems under Partial Observation. II Drift term., in: ALEA (Latin American Journal of Probability and Statistics), 2014, vol. 11, no 1, pp. 359-384.

    https://hal.archives-ouvertes.fr/hal-00877054
  • 42P. Cattiaux, J. R. Leon, C. Prieur.

    Recursive Estimation for Stochastic Damping Hamiltonian Systems, October 2014, To appear in Journal of Nonparametric Statistics..

    https://hal.archives-ouvertes.fr/hal-01071252
  • 43M. Champion, G. Chastaing, S. Gadat, C. Prieur.

    L2 Boosting on generalized Hoeffding decomposition for dependent variables. Application to Sensitivity Analysis, 2013, 48 pages, 7 Figures.
  • 44G. Chastaing.

    Generalized Sobol sensitivity indices for dependent variables, Université de Grenoble, September 2013.

    https://tel.archives-ouvertes.fr/tel-00930229
  • 45G. Chastaing, F. Gamboa, C. Prieur.

    Generalized Hoeffding-Sobol Decomposition for Dependent Variables - Application to Sensitivity Analysis, in: Electronic Journal of Statistics, December 2012, vol. 6, pp. 2420-2448. [ DOI : 10.1214/12-EJS749 ]

    http://hal.archives-ouvertes.fr/hal-00649404
  • 46G. Chastaing, C. Prieur, F. Gamboa.

    Generalized Sobol sensitivity indices for dependent variables: numerical methods, March 2013.

    http://hal.inria.fr/hal-00801628
  • 47A. Cousin, E. Di Bernardino.

    On multivariate extensions of Value-at-Risk, in: J. Multivariate Anal., 2013, vol. 119, pp. 32–46.

    http://dx.doi.org/10.1016/j.jmva.2013.03.016
  • 48C. De Michele, G. Salvadori, R. Vezzoli, S. Pecora.

    Multivariate assessment of droughts: Frequency analysis and dynamic return period, in: Water Resources Research, 2013, vol. 49, no 10, pp. 6985–6994.
  • 49E. Di Bernardino, T. Laloë, V. Maume-Deschamps, C. Prieur.

    Plug-in estimation of level sets in a non-compact setting with applications in multivariate risk theory, in: ESAIM: Probability and Statistics, February 2013, vol. 17, pp. 236-256. [ DOI : 10.1051/ps/2011161 ]

    http://hal.inria.fr/hal-00580624
  • 50E. Di Bernardino, V. Maume-Deschamps, C. Prieur.

    Estimating Bivariate Tail: a copula based approach, in: Journal of Multivariate Analysis, 2013, vol. 119, pp. 81-100.

    http://hal.inria.fr/hal-00475386
  • 51E. Di Bernardino, C. Prieur.

    Estimation of Multivariate Conditional Tail Expectation using Kendall's Process, October 2012.

    http://hal.archives-ouvertes.fr/hal-00740340
  • 52F. Gamboa, A. Janon, T. Klein, A. Lagnoux-Renaudie, C. Prieur.

    Statistical inference for Sobol pick freeze Monte Carlo method, March 2013.

    http://hal.inria.fr/hal-00804668
  • 53W. Hoeffding.

    A class of statistics with asymptotically normal distribution, in: Ann. Math. Statistics, 1948, vol. 19, pp. 293–325.
  • 54A. Janon, T. Klein, A. Lagnoux-Renaudie, M. Nodet, C. Prieur.

    Asymptotic normality and efficiency of two Sobol index estimators, in: ESAIM: Probability and Statistics, October 2014, vol. 18, pp. 342-364. [ DOI : 10.1051/ps/2013040 ]

    https://hal.inria.fr/hal-00665048
  • 55A. Janon, M. Nodet, C. Prieur.

    Certified reduced-basis solutions of viscous Burgers equation parametrized by initial and boundary values, in: ESAIM: Mathematical Modelling and Numerical Analysis, March 2013, vol. 47, no 2, pp. 317-348. [ DOI : 10.1051/m2an/2012029 ]

    http://hal.inria.fr/inria-00524727
  • 56A. Janon, M. Nodet, C. Prieur.

    Uncertainties assessment in global sensitivity indices estimation from metamodels, in: International Journal for Uncertainty Quantification, 2014, vol. 4, no 1, pp. 21-36. [ DOI : 10.1615/Int.J.UncertaintyQuantification.2012004291 ]

    https://hal.inria.fr/inria-00567977
  • 57M. Kennedy, A. O'Hagan.

    Predicting the output from a complex computer code when fast approximations are available, in: Biometrika, 2000, vol. 87, pp. 1–13.
  • 58F. Lemarié, L. Debreu, E. Blayo.

    Optimal control of the convergence rate of Global-in-time Schwarz algorithms, in: Domain Decomposition Methods in Science and Engineering XX, R. Bank, M. Holst, O. Widlund, J. Xu (editors), volume 91 of Lecture Notes in Computational Science and Engineering, Springer-Verlag Berlin Heidelberg, 2013, pp. 599-606. [ DOI : 10.1007/978-3-642-35275-1_71 ]

    https://hal.archives-ouvertes.fr/hal-00661979
  • 59F. Lemarié, L. Debreu, E. Blayo.

    Toward an Optimized Global-in-Time Schwarz Algorithm for Diffusion Equations with Discontinuous and Spatially Variable Coefficients, Part 1: The Constant Coefficients Case, in: Electronic Transactions on Numerical Analysis, 2013, vol. 40, pp. 148-169.

    https://hal.archives-ouvertes.fr/hal-00661977
  • 60F. Lemarié, L. Debreu, E. Blayo.

    Toward an Optimized Global-in-Time Schwarz Algorithm for Diffusion Equations with Discontinuous and Spatially Variable Coefficients, Part 2: the Variable Coefficients Case, in: Electronic Transactions on Numerical Analysis, 2013, vol. 40, pp. 170-186.

    https://hal.archives-ouvertes.fr/hal-00661978
  • 61F. Lemarié, P. Marchesiello, L. Debreu, E. Blayo.

    Sensitivity of Ocean-Atmosphere Coupled Models to the Coupling Method : Example of Tropical Cyclone Erica, Inria Grenoble ; Inria, December 2014, no RR-8651, 32 p.

    https://hal.inria.fr/hal-00872496
  • 62A. Makris, C. Prieur.

    Bayesian Multiple Hypothesis Tracking of Merging and Splitting Targets, in: IEEE Transactions on Geoscience and Remote Sensing, 2014, vol. 52, no 12, pp. 7684-7694. [ DOI : 10.1109/TGRS.2014.2316600 ]

    https://hal.inria.fr/hal-00919018
  • 63S. Nanty, C. Helbert, A. Marrel, N. Pérot, C. Prieur.

    Uncertainy quantification for functional dependent random variables, 2014, working paper or preprint.

    https://hal.archives-ouvertes.fr/hal-01075840
  • 64A. Owen.

    Variance components and generalized sobol' indices, 2012.

    http://arxiv.org/abs/1205.1774
  • 65Z. Qian, C. C. Seepersad, V. R. Joseph, J. K. Allen, C. F. J. Wu.

    Building surrogate models based on detailed and approximate simulations, in: Journal of Mechanical Design, 2006, vol. 128, no 4, pp. 668-677.
  • 66A. Saltelli.

    Making best use of model evaluations to compute sensitivity indices, in: Computer Physics Communications, 2002, vol. 145, no 2, pp. 280 - 297. [ DOI : 10.1016/S0010-4655(02)00280-1 ]

    http://www.sciencedirect.com/science/article/pii/S0010465502002801
  • 67G. Salvadori, C. De Michele, F. Durante.

    On the return period and design in a multivariate framework, in: Hydrology and Earth System Sciences, 2011, vol. 15, no 11, pp. 3293–3305.
  • 68I. M. Sobol.

    Sensitivity estimates for nonlinear mathematical models, in: Math. Modeling Comput. Experiment, 1993, vol. 1, no 4, pp. 407–414 (1995).
  • 69I. Souopgui.

    Assimilation d'images pour les fluides géophysiques, Université Joseph-Fourier - Grenoble I, Oct 2010.
  • 70C. B. Storlie, T. C. M. Lee, J. Hannig, D. Nychka.

    Tracking of multiple merging and splitting targets: a statistical perspective, in: Statist. Sinica, 2009, vol. 19, no 1, pp. 1–31.
  • 71J.-Y. Tissot, C. Prieur.

    A randomized Orthogonal Array-based procedure for the estimation of first- and second-order Sobol' indices, in: Journal of Statistical Computation and Simulation, 2014, pp. 1-24. [ DOI : 10.1080/00949655.2014.971799 ]

    https://hal.archives-ouvertes.fr/hal-00743964
  • 72F. Zertuche, C. Helbert, A. Antoniadis.

    Multi-fidelity regression using a non-parametric relationship, in: MASCOT 2014 - Méthodes d'Analyse Statistique pour les COdes et Traitements numériques, Zurich, Switzerland, April 2014.

    https://hal.archives-ouvertes.fr/hal-01096661


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