Research themes:
- Nonparametric estimation
- Inverse problems
- Frequentist and Bayesian approaches
- High-dimensional statistics
- Wavelets and approximation theory
- Multivariate point processes
- Statistics for biology, genetics and neuroscience
SUBMITTED ARTICLES:
PUBLICATIONS:
- Belhakem R., Picard F., Rivoirard V. and Roche A. (2024) Minimax estimation of Functional Principal Components from noisy discretized functional data (43 pages) To appear in Scandinavian Journal of Statistics
- Sulem D., Rivoirard V. and Rousseau J. (2024) Bayesian estimation of nonlinear Hawkes processes. Published in Bernoulli, 30, no 2, 1257-1286. Supplementary file (49 pages)
- Nguyen T.D., Pham Ngoc T.M. and Rivoirard V. (2023) Adaptive warped kernel estimation for nonparametric regression with circular responses. Published in Electronic Journal of Statistics, 17, no 2, 4011-4048
- Varet S, Lacour C., Massart P. and Rivoirard V. (2023) Numerical performance of Penalized Comparison to Overfitting for multivariate kernel density estimation. Published in ESAIM PS, 27, 621-667
- Nguyen M.L.J., Lacour C. and Rivoirard V (2022) Adaptive greedy algorithm for moderately large dimensions in kernel conditional density estimation. Published in Journal of Machine Learning Research, 23, no 254, 1-74
- Hoang V.H., Pham Ngoc T.M., Rivoirard V. and Tran V.C. (2022) Nonparametric estimation of the fragmentation kernel based on a partial differential equation stationary distribution approximation. Published in Scandinavian Journal of Statistics, 49, no 1, 4-43
- Maïda M., Nguyen T.D., Pham Ngoc T.M., Rivoirard V. and Tran V.C. (2022) Statistical deconvolution of the free Fokker-Planck equation at fixed time. Published in Bernoulli, 28, no 2, 771-802. Supplementary file (13 pages)
- Bonnet A., Lacour C., Picard F. and Rivoirard V. (2022) Uniform Deconvolution for Poisson Point Processes. Published in Journal of Machine Learning Research, 23, no 194, 1-36
- Browning R., Sulem D., Mengersen K, Rivoirard V. and Rousseau J. (2021) Simple discrete-time self-exciting models can describe complex dynamic processes: A case study of COVID-19. Published in PLoS ONE, 16, no 4, 1-28
- Donnet S., Rivoirard V. and Rousseau J. (2020) Nonparametric Bayesian estimation of multivariate Hawkes processes Published in Annals of Statistics, 48, no 5, 2698-2727. Supplementary file (29 pages)
- Hunt X. J., Reynaud-Bouret P., Rivoirard V., Sansonnet L. and Willet R. (2019) A data-dependent weighted LASSO under Poisson noise Published in IEEE Transactions on Information Theory, 65, no 3, 1589-1613
- Lambert R., Tuleau-Malot C., Bessaih T., Rivoirard V., Bouret Y., Leresche N. and Reynaud-Bouret P. (2018) Reconstructing the functional connectivity of multiple spike trains using Hawkes models Published in the Journal of Neuroscience Methods, 297, 9-21
- Donnet S., Rivoirard V., Rousseau J. and Scricciolo C. (2018) Posterior concentration rates for empirical Bayes procedures, with applications to Dirichlet Process mixtures Published in Bernoulli, 24, no 1, 231-256. Supplementary file (13 pages)
- Lacour C., Massart P. and Rivoirard V. (2017) Estimator selection: a new method with applications to kernel density estimation Published in Sankhya A (special issue on Application of concentration inequalities and empirical processes to modern statistics), 79, no 2, 298-335
- Chichignoud M., Hoang V.H., Pham Ngoc T.M. and Rivoirard V. (2017) Adaptive wavelet multivariate regression with errors in variables Published in Electronic Journal of Statistics, 11, no 1, 682-724
- Donnet S., Rivoirard V., Rousseau J. and Scricciolo C. (2017) Posterior concentration rates for counting processes with Aalen multiplicative intensities Published in Bayesian Analysis, 12, no 1, 53-87. Supplementary file (8 pages)
- Ivanoff S., Picard F. and Rivoirard V. (2016) Adaptive Lasso and group-Lasso for functional Poisson regression Published in Journal of Machine Learning Research, 17, no 55, 1-46
- Bertin K., Lacour C. and Rivoirard V. (2016) Adaptive pointwise estimation of conditional density function Published in Les Annales de l'IHP, 52, no 2, 939-980
- Hansen N.R., Reynaud-Bouret P. and Rivoirard V. (2015) Lasso and probabilistic inequalities for multivariate point processes Published in Bernoulli, 21, no 1, 83-143
- Reynaud-Bouret P., Rivoirard V., Grammont F. and Tuleau-Malot C. (2014) Goodness-of-fit tests and nonparametric adaptive estimation for spike train analysis Published in Journal of Mathematical Neuroscience, 4:3, 1-41. Supplementary file 1 (9 pages) Supplementary file 2 (5 pages) Supplementary file 3 (3 pages)
- Arribas-Gil A., Bertin K., Meza C. and Rivoirard V. (2014) Lasso-type estimators for semiparametric nonlinear mixed-effects models estimation Published in Statistics and Computing, 24, no 3, 443-460. Supplementary file (12 pages)
- Pham Ngoc T.M. and Rivoirard V. (2013) The dictionary approach for spherical deconvolution Published in Journal of Multivariate Analysis, 115, 138-156
- Rivoirard V. and Rousseau J. (2012) Bernstein - von Mises theorem for linear functionals of the density Published in Annals of Statistics, 40, no 3, 1489-1523
- Rivoirard V. and Rousseau J. (2012) Posterior concentration rates for infinite dimensional exponential families Published in Bayesian Analysis, 7, no 2, 311-334
- Doumic M., Hoffmann M., Reynaud-Bouret P. and Rivoirard V. (2012) Nonparametric estimation of the division rate of a size-structured population Published in SIAM Journal on Numerical Analysis, 50, no. 2, 925-950
- Bertin K., Le Pennec E. and Rivoirard V. (2011) Adaptive Dantzig density estimation Published in Les Annales de l'IHP, 47, no. 1, 43-74
- Reynaud-Bouret P., Rivoirard V. and Tuleau-Malot C. (2011) Adaptive density estimation: a curse of support? Published in Journal of Statistical Planning and Inference, 141, 115-139
- Reynaud-Bouret P. and Rivoirard V. (2010) Near optimal thresholding estimation of a Poisson intensity on the real line Published in Electronic Journal of Statistics, 4, 172-238
- Autin F., Le Pennec E., Loubes J.M. and Rivoirard V. (2010) Maxisets for model selection Published in Constructive approximation, 31, no. 2, 195-229
- Bertin K. and Rivoirard V. (2009) Maxiset in sup-norm for kernel estimators Published in Test, 18, no. 3, 475-496
- Loubes J.M. and Rivoirard V. (2009) Review of rates of convergence and regularity conditions for inverse problems Published in International Journal of Tomography & Statistics, 11, no. S09, 61-82
- Rivoirard V. and Tribouley K. (2008) The maxiset point of view for estimating integrated quadratic functionals Published in Statistica Sinica, 18, no. 1, 255-279
- Autin F., Picard D. and Rivoirard V. (2006) Large variance Gaussian priors in Bayesian nonparametric estimation: a maxiset approach Published in Mathematical Methods of Statistics, 15, no. 4, 349-373
- Rivoirard V. (2006) Non linear estimation over weak Besov spaces and minimax Bayes method Published in Bernoulli, 12, no. 4, 609-632
- Rivoirard V. (2005) Bayesian modelling of sparse sequences and maxisets for Bayes rules Published in Mathematical Methods of Statistics, 14, no. 3, 346-376.
- Rivoirard V. (2004) Thresholding procedure with priors based on Pareto distributions Published in Test, 13, no. 1, 213-246
- Rivoirard V. (2004) Maxisets for linear procedures Published in Statistics and Probability Letters, 67, no. 3, 267-275
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