- FR
- EN
Judith Rousseau is currently a professor of statistics at CEREMADE at Paris Dauphine University – PSL and is affiliated with the University of Oxford. Her research covers the theoretical aspects of Bayesian procedures, as well as more methodological developments. From a theoretical perspective, she is interested in the interfaces between Bayesian and frequentist approaches and machine learning methods. A significant portion of her work focuses on the study of the frequentist properties of Bayesian methods; she also works on the links between Bayesian uncertainty quantification, machine learning, and generative models. She has also conducted more methodological research on MCMC and related algorithms, as well as on the elicitation of subjective prior distributions.
She has held numerous leadership roles within several learned societies. Notably, she is currently President-Elect of the International Society of Bayesian Analysis (ISBA). She is a fellow of the ISBA and the IMS, and received the Ethel Newbold Prize in 2015. She delivered a Medallion Lecture in 2017, received a European Research Council Advanced Grant in 2019, delivered the Le Cam Lecture in 2025, and will give a “sectional lecture” at the International Congress of Mathematicians (ICM) in July 2026.
(2026), Nonparametric Bayesian intensity estimation for covariate-driven inhomogeneous point processes, Bernoulli, vol. 32, n°2, p. 1020 - 1044 
(2025), Nonparametric Regression on Random Geometric Graphs Sampled from Submanifolds, Journal of Machine Learning Research, vol. 26, n°164, p. 1−65
(2025), Scalable and Adaptive Variational Bayes Methods for Hawkes Processes, Journal of Machine Learning Research, vol. 26, n°217, p. 1-102
(2024), Estimating a density near an unknown manifold: A Bayesian nonparametric approach, Annals of Statistics, vol. 52, n°5, p. 2081-2111
(2024), Asymptotic Analysis of Statistical Estimators related to MultiGraphex Processes under Misspecification, Bernoulli, vol. 30, n°4, p. 2644-2675
(2024), Bayesian estimation of nonlinear Hawkes processes, Bernoulli, vol. 30, n°2, p. 1257–1286
(2024), Wasserstein convergence in Bayesian and frequentist deconvolution models, Annals of Statistics, vol. 52, n°4, p. 1691-1715
(2024), Efficient Bayesian estimation and use of cut posterior in semiparametric hidden Markov models, Electronic Journal of Statistics, vol. 18, n°1, p. 1815-1886
(2024), Ideal Bayesian Spatial Adaptation, Journal of the American Statistical Association, vol. 119, n°547, p. 2078-2091
(2023), A special issue on Bayesian Inference: Challenges, Perspective, and Prospects, Philosophical Transactions. Physical, Mathematical and Engineering Sciences, vol. 381, n°2247
(2023), On sparsity, power-law, and clustering properties of graphex processes, Advances in Applied Probability, vol. 55, n°4, p. 1211-1253
(2021), Simple discrete-time self-exciting models can describe complex dynamic processes: A case study of COVID-19, PLoS ONE, vol. 16, n°4
(2020), Model Misspecification in ABC: Consequences and Diagnostics, Journal of the Royal Statistical Society. Series B, Statistical Methodology, vol. 82, n°2, p. 421-444
(2020), Nonparametric Bayesian estimation for multivariate Hawkes processes, Annals of Statistics, vol. 48, n°5, p. 2698-2727
(2018), Asymptotic Properties of Approximate Bayesian Computation, Biometrika, vol. 105, n°3, p. 593-607
(2018), Efficient semiparametric estimation and model selection for multidimensional mixtures, Electronic Journal of Statistics, vol. 12, n°1, p. 703-740
(2018), Posterior concentration rates for empirical Bayes procedures, with applications to Dirichlet Process mixtures, Bernoulli, vol. 24, n°1, p. 231-256
(2017), How Principled and Practical Are Penalised Complexity Priors?, Statistical Science, vol. 32, n°1, p. 36-40
(2017), Posterior concentration rates for counting processes with Aalen multiplicative intensities, Bayesian Analysis, vol. 12, n°1, p. 53-87
(2017), Posterior concentration rates for mixtures of normals in random design regression, Electronic Journal of Statistics, vol. 11, n°2, p. 4065-4102
(2016), Bayesian Inference for Partially Observed Multiplicative Intensity Processes, Bayesian Analysis, vol. 11, n°1, p. 151-190
(2016), Nonparametric Bayesian Clay for Robust Decision Bricks, Statistical Science, vol. 31, n°4, p. 506-510
(2016), Bayesian nonparametric dependent model for partially replicated data: The influence of fuel spills on species diversity, Annals of Applied Statistics, vol. 10, n°3, p. 1496-1516
(2016), Nonparametric finite translation hidden Markov models and extensions, Bernoulli, vol. 22, n°1, p. 193-212
(2016), On the Frequentist Properties of Bayesian Nonparametric Methods, Annual Reviews of Statistics and its applications, vol. 3:211-231, p. 24
(2015), A note on Bayes factor consistency in partial linear models, Journal of Statistical Planning and Inference, vol. 166, p. 158-170
(2015), Overfitting Bayesian Mixture Models with an Unknown Number of Components., PLoS ONE, vol. 10, n°7, p. e0131739
(2015), A Bernstein-von Mises theorem for smooth functionals in semiparametric models, Annals of Statistics, vol. 43, n°6, p. 2353-2383
(2015), On adaptive posterior concentration rates, Annals of Statistics, vol. 43, n°5, p. 2259-2295
(2014), About the posterior distribution in hidden Markov models with unknown number of states, Bernoulli, vol. 20, n°4, p. 2039-2075
(2014), Relevant statistics for Bayesian model choice, Journal of the Royal Statistical Society. Series B, Statistical Methodology, vol. 76, n°5, p. 833-859
(2014), Empirical Bayes methods in classical and Bayesian inference, Metron, vol. 72, n°2, p. 201-215
(2014), Bayes and empirical Bayes : Do they merge?, Biometrika, vol. 101, n°2, p. 285-302
(2014), Using informative priors in the estimation of mixtures over time with application to aerosol particle size distributions, Annals of Applied Statistics, vol. 8, n°1, p. 232-258
(2013), Bayesian semi-parametric estimation of the long-memory parameter under FEXP-priors, Electronic Journal of Statistics, vol. 7, p. 2947-2969
(2013), Bayesian Optimal Adaptive Estimation Using a Sieve Prior, Scandinavian Journal of Statistics, vol. 40, n°3, p. 549-570
(2013), Inherent difficulties of non-Bayesian likelihood-based inference, as revealed by an examination of a recent book by Aitkin, Statistics & Risk Modeling, vol. 30, n°2, p. 105-120
(2013), Computational aspects of Bayesian spectral density estimation, Journal of Computational and Graphical Statistics, vol. 22, n°3, p. 533-557
(2012), Bernstein–von Mises theorem for linear functionals of the density, Annals of Statistics, vol. 40, n°3, p. 1489-1523
(2012), Combining Expert Opinions in Prior Elicitation, Bayesian Analysis, vol. 7, n°3, p. 503-532
(2012), Bayesian nonparametric estimation of the spectral density of a long or intermediate memory Gaussian process, Annals of Statistics, vol. 40, n°2, p. 964-995
(2012), Asymptotic Theory for Maximum Likelihood Estimation of the Memory Parameter in Stationary Gaussian Processes, Econometric Theory, vol. 28, n°2, p. 457-470
(2012), Posterior concentration rates for infinite dimensional exponential families, Bayesian Analysis, vol. 7, n°2, p. 311-334
(2011), Asymptotic behaviour of the posterior distribution in overfitted mixture models, Journal of the Royal Statistical Society. Series B, Statistical Methodology, vol. 73, n°5, p. 689-710
(2010), Rates of convergence for the posterior distributions of mixtures of Betas and adaptive nonparametric estimation of the density, Annals of Statistics, vol. 38, n°1, p. 146-180
(2009), Rejoinder: Harold Jeffreys' Theory of Probability Revisited, Statistical Science, vol. 24, n°2, p. 191-194
(2009), Bayesian Goodness-of-Fit Testing with Mixtures of Triangular Distributions, Scandinavian Journal of Statistics, vol. 36, p. 337-354
(2009), Intracerebral delivery of 5-iodo-2'-deoxyuridine in combination with synchrotron stereotactic radiation for the therapy of the F98 glioma., Journal of Synchrotron Radiation, vol. 16, n°Pt 4, p. 573-581
(2009), Harold Jeffreys' Theory of Probability revisited, Statistical Science, vol. 24, n°2, p. 141-172
(2009), Bayesian hidden Markov Model for DNA segmentation : A prior sensitivity analysis, Computational Statistics & Data Analysis, vol. 53, n°5, p. 1873-1882
(2008), Bounds for Bayesian order identification with application to mixtures, Annals of Statistics, vol. 36, n°2, p. 938-962
(2008), Studentization and deriving accurate p-values, Biometrika, vol. 95, n°1, p. 1-16
(2008), Quantitative Risk Assessment from Farm to Fork and Beyond: A Global Bayesian Approach Concerning Food-Borne Diseases, Risk Analysis, vol. 28, n°2, p. 557-571
(2008), Encoding expert opinion on skewed non-negative distributions, Journal of Applied Probability and Statistics , vol. 3, n°1, p. 1-21
(2007), Consistency results on nonparametric Bayesian estimation of level sets using spatial priors, Test, vol. 16, n°1, p. 90-108
(2005), Rates of Convergence for a Bayesian Level Set Estimation, Scandinavian Journal of Statistics, vol. 32, n°4, p. 639-660
(2004), Optimal Sample Size for Multiple Testing: The Case of Gene Expression Microarrays, Journal of the American Statistical Association, vol. 99, n°468, p. 990-1001
(2012), Hidden Markov models for complex stochastic processes: A case study in electrophysiology., in Pettitt, Anthony N., Case Studies in Bayesian Statistical Modelling and Analysis Wiley, p. 598
(2011), Bayesian Inference and Computation, in Stumpf, Michael, Handbook of Statistical Systems Biology Wiley, p. 600
(2010), On Bayesian Data Analysis, in Böcker, Klaus, Rethinking Risk Measurement and Reporting, London: Infopro Digital Risk Ltd, p. 527
(2014), On some aspects of the asymptotic properties of Bayesian approaches in nonparametric and semiparametric models, in , ESAIM - Journée MAS 2012, Clermont-Ferrand, ESAIM: Proceedings and Surveys, 159-171 p.
(2007), Approximating Interval hypothesis : p-values and Bayes factors, in West, M., Valencia International Meeting on Bayesian Statistics 2006, Oxford, Oxford University Press, 688 p.
(2023), Posterior Contraction Rates for Matérn Gaussian Processes on Riemannian Manifolds, NeurIPS 2023, La Nouvelle-Orléans, États-Unis
(2014), On Convergence Rates of Empirical Bayes Procedures, SIS 2014, Cagliari, Italie
(2014), Non parametric Bayesian estimation for Hawkes processes, International Society for Bayesian Analysis World Meeting, ISBA 2014, Cancun, Mexique
(2014), On consistency issues in Bayesian nonparametric testing - a review, SIS 2014, Cagliari, Italie
(2014), On diversity under a Bayesian nonparametric dependent model, SIS 2014, Cagliari, Italie
(2010), Bayesian Nonparametric Inference of Decreasing Densities, 42èmes Journées de Statistique, Marseille, France
(2010), On Bayesian Estimation of the Long-Memory Parameter in the FEXP-Model for Gaussian Time Series, 9th Valencia International Meeting on Bayesian Statistics - 2010 World Meeting of the International Society for Bayesian Analysis, Benidorm, Espagne
(2010), How Should We Combine Expert Opinions: On Elicitation, Encoding, Priors or Posteriors?, 9th Valencia International Meeting on Bayesian Statistics - 2010 World Meeting of the International Society for Bayesian Analysis, Benidorm, Espagne
(2010), Asymptotic Behaviour of the Posterior Distribution in Mixture Models with too many Components, 9th Valencia International Meeting on Bayesian Statistics - 2010 World Meeting of the International Society for Bayesian Analysis, Benidorm, Espagne
(2009), Adaptive Bayesian Density Estimation with Location-Scale Mixtures, 7th Workshop on Bayesian Nonparametrics, Moncalieri, Italie
(2009), Rates of convergence for the posterior distributions of mixtures of betas and adaptive nonparamatric estimation of the density, 7th Workshop on Bayesian Nonparametrics, Moncalieri, Italie
(2007), A global Bayesian approach for quantitative risk assessment (QRA) from farm to illness - application to campylobacteriosis through broiler, 5th International Conference of Predictive Modelling in Food, Athenes, Grèce
(2024), Convergence of Diffusion Models Under the Manifold Hypothesis in High-Dimensions, Paris, Preprints Ceremade
(2022), Asymptotic Analysis of Statistical Estimators related to MultiGraphex Processes under Misspecification, Paris, Cahier de recherche CEREMADE, Université Paris Dauphine-PSL, 79 p.
(2022), Evidence estimation in finite and infinite mixture models and applications, Paris, Cahier de recherche CEREMADE, Université Paris Dauphine-PSL, 43 p.
(2017), Testing hypotheses via a mixture estimation model, Paris, Cahier de recherche CEREMADE, Université Paris Dauphine-PSL, 37 p.
(2016), Some comments about A Bayesian criterion for singular models by M. Drton and M. Plummer, Paris, Cahier de recherche CEREMADE, Université Paris Dauphine-PSL, 4 p.
(2014), Posterior concentration rates for empirical Bayes procedures, with applications to Dirichlet Process mixtures. Supplementary material, Paris, Université Paris-Dauphine, 4 p.
(2014), Bayesian matrix completion: prior specification and consistency, Paris, Université Paris-Dauphine, 26 p.
(2013), Non parametric finite translation mixtures with dependent regime, Paris, Université Paris-Dauphine, 26 p.
(2012), Bayes factor consistency in regression problems, Paris, Université Paris-Dauphine, 22 p.
(2011), Evaluating statistic appropriateness for Bayesian model choice, Paris, Université Paris-Dauphine, 18 p.
(2011), Adaptive Bayesian Estimation of a spectral density, Paris, Université Paris-Dauphine, 14 p.
(2006), Bayesian nonparametric estimation of the spectral density of a long memory Gaussian time series, Paris, Cahiers du CEREMADE, 51 p.
(2005), Developing p-values: a Bayesian-frequentist convergence, Paris, Cahiers du CEREMADE, 16 p.
(2005), Bayesian Mixtures of Triangular distributions with application to Goodness-of-Fit Testing, Paris, Cahiers du CEREMADE, 45 p.
(2002), A Mixture Approach to Bayesian Goodness of Fit, Paris, Université Paris-Dauphine, 25 p.
