Theory

  • C. Amorino, E. Nualart, F. Panloup, J. Sieber. Fast convergence rates for estimating the stationary density in SDEs driven by a fractional Brownian motion with semi-contractive drift. — Annals of Statistics, forthcoming, 2026.
  • M. Foondun, D. Khoshnevisan, E. Nualart. On the local well-posedness of randomly forced reaction-diffusion equations with L^2 initial data and a superlinear reaction term. — Probability Theory and Related Fields, forthcoming, 2026.
  • P. Zwiernik. Entropic covariance models. — Annals of Statistics, 2025.
  • C. Amorino, A. Gloter. Minimax rate for multivariate data under componentwise local differential privacy constraints. — Annals of Statistics, 2025.
  • C. Amorino, D. Belomestny, V. Pilipauskaitė, M. Podolskij, S. Zhou. Polynomial rates via deconvolution for nonparametric estimation in McKean–Vlasov SDEs. — Probability Theory and Related Fields, 2025.
  • M. Foondun, D. Khoshnevisan, E. Nualart. Instantaneous everywhere-blow-up of parabolic SPDEs. — Probability Theory and Related Fields, 2024.
  • G. Mesters, P. Zwiernik. Non-independent component analysis. — Annals of Statistics, 2024.
  • N. Broutin, N. Kamčev, G. Lugosi. Increasing paths in random temporal graphs. — Annals of Applied Probability, 2024.
  • D. Rossell, A. K. Kseung, I. Saez, M. Guindani. Semi-parametric local variable selection under misspecification. — Biometrika, 2024.
  • L. Cappello, A. Véber, J. A. Palacios. An efficient coalescent model for heterochronously sampled molecular data. — Journal of the American Statistical Association, 2024.
  • F. Röttger, S. Engelke, P. Zwiernik. Total positivity in multivariate extremes. — Annals of Statistics, 2023.
  • L. Cappello, O. H. Madrid Padilla, J. A. Palacios. Bayesian change-point detection with spike-and-slab priors. — Journal of Computational and Graphical Statistics, 2023.
  • J. Jewson, D. Rossell. Loss function selection and the use of improper models. — JRSS B, 2022.
  • S. Lauritzen, P. Zwiernik. Locally associated graphical models and mixed convex exponential families. — Annals of Statistics, 2022.
  • G. Lugosi, S. Mendelson. Multivariate mean estimation with direction-dependent accuracy. — Journal of the European Mathematical Society, 2022.
  • L. Addario-Berry, L. Devroye, G. Lugosi, V. Velona. Broadcasting on random recursive trees. — Annals of Applied Probability, 2022.
  • D. Rossell. Concentration of posterior probabilities and normalized L0 criteria. — Bayesian Analysis, 2022.
  • A. Avalos-Pacheco, D. Rossell, R. Savage. Heterogeneous large datasets integration using Bayesian factor regression. — Bayesian Analysis, 2022.
  • L. Cappello, J. A. Palacios. Adaptive preferential sampling in phylodynamics. — Journal of Computational and Graphical Statistics, 2022.
  • G. Lugosi, J. Truszkowski, V. Velona, P. Zwiernik. Learning partial correlation graphs by covariance queries. — Journal of Machine Learning Research, 2021.
  • D. Rossell, O. Abril, A. Bhattacharya. Approximate Laplace approximations for scalable model selection. — JRSS B, 2021.
  • G. Lugosi, S. Mendelson. Robust multivariate mean estimation: the optimality of trimmed mean. — Annals of Statistics, 2021.
  • S. Lauritzen, C. Uhler, P. Zwiernik. Total positivity in exponential families with application to binary variables. — Annals of Statistics, 2021.
  • D. Rossell, F. J. Rubio. Additive Bayesian variable selection under censoring and misspecification. — Statistical Science, 2021.
  • D. Rossell, P. Zwiernik. Dependence in elliptical partial correlation graphs. — Electronic Journal of Statistics, 2021.
  • C. Bordenave, G. Lugosi, N. Zhivotovskiy. Noise sensitivity of the top eigenvector of a Wigner matrix. — Probability Theory and Related Fields, 2020.
  • G. Lugosi, S. Mendelson. Risk minimization by median-of-means tournaments. — Journal of the European Mathematical Society, 2020.
  • P. L. Bartlett, P. L. Long, G. Lugosi, A. Tsigler. Benign overfitting in linear regression. — PNAS, 2020.

Applications

  • L. Cappello, Lo W.T.J., Zhang J.Z., Xu P., Barrow D., Chopra I., Clark A.G., Wells M.T., Kim J. Bayesian phylodynamic inference of population dynamics with dormancy. — PNAS, 2025.
  • J. Jewson, L. Li, L. Battaglia, S. Hansen, D. Rossell, P. Zwiernik. Graphical model inference with external network data. — Biometrics, 2024.
  • L. Cappello, J. Kim, S. Liu, J. A. Palacios. Statistical challenges in tracking the evolution of SARS-CoV-2. — Statistical Science, 2022.
  • C. Semken, D. Rossell. Specification analysis for technology use and teenager well-being. — JRSS C, 2022.
  • V. Parikh et al., L. Cappello, M. Ashley. Multi-omic strategy for COVID-19 severity. — Nature Communications, 2022.
  • L. Beauchemin, M. Slifker, D. Rossell, J. Font-Burgada. Characterizing MHC-I genotype predictive power for oncogenic mutation probability in cancer patients. — Springer (Methods & Protocols), 2020.
  • M. Graeve, M. Greenacre. The selection and analysis of fatty-acid ratios in marine pelagic organisms. — Limnology and Oceanography: Methods, 2020.
  • M. Greenacre. Amalgamations are valid in compositional data analysis and their log-ratios have an inverse transform. — Applied Computing and Geosciences, 2020.
  • R. Gavard, H. Jones, D. Palacio Lozano, M. Thomas, D. Rossell, S. Spencer, M. Barrow. KairosMS: A new solution for processing hyphenated UH-resolution mass-spectrometry data. — Analytical Chemistry, 2020.