Engelke S., Ivanovs J. & Strokorb K.
Graphical models for infinite measures with applications to extremes and Lévy processes. [arxiv]
Hentschel M., Engelke S. & Segers J.
Statistical inference for Hüsler-Reiss graphical models through matrix completions. [arxiv]
Best Student Paper Award at the EVA conference 2023 for Manuel Hentschel
Pasche O. & Engelke S.
Neural networks for extreme quantile regression with an application to forecasting of flood risk. [arxiv]
Engelke S., Lalancette M. & Volgushev S.
Learning extremal graphical structures in high dimensions. [arxiv]
Gnecco N., Terefe E.M., & Engelke S.
Extremal random forests. [arxiv]
Deidda C., Engelke S., & De Michele, C.
Asymmetric dependence in hydrological extremes. [arxiv]
Birghila C., Aigner M. & Engelke S.
Distributionally robust tail bounds based on Wasserstein distance and f-divergence. [arxiv]
Kimber T., Engelke S., Tetko I., Bruno E. & Godin G.
Synergy effect between convolutional neural networks and the multiplicity of SMILES for improvement of molecular prediction. [arxiv]
Dombry C., Engelke S. & Oesting M.
Asymptotic properties of likelihood estimators for multivariate extreme value distributions. [arxiv]
Zeder J., Sippel S., Pasche O., Engelke S., & E. Fischer (2023)
The effect of a short observational record on the statistics of temperature extremes.
Geophysical Research Letters, 50, e2023GL10409.
Röttger F., Engelke S. & Zwiernik P. (2023)
Total positivity in multivariate extremes.
Annals of Statistics, to appear. [arxiv]
Velthoen J., Dombry C., Cai J.-J., & Engelke S. (2023)
Gradient boosting for extreme quantile regression.
Extremes, to appear. [arxiv]
Bai Y., Lam H. & Engelke S. (2022)
Rare-event simulation without variance reduction: an extreme value theory approach.
IEEE 2022 Winter Simulation Conference, 49, 133-144.
WSC PhD Colloquium INFORMS I-SIM Award 2022
Boulaguiem Y., Zscheischler J., Vignotto E., van der Wiel K. & Engelke S. (2022)
Modelling and simulating spatial extremes by combining extreme value theory with generative adversarial networks.
Environmental Data Science, to appear. [arxiv]
Lalancette M., Engelke S. & Volgushev S. (2021)
Rank-based estimation under asymptotic dependence and independence, with applications to spatial extremes.
Annals of Statistics, 49, 2552-2576.
[arxiv]
Gnecco N., Meinshausen N., Peters J. & Engelke S. (2021)
Causal discovery in heavy-tailed models.
Annals of Statistics, 49: 1755-1778. [arxiv]
Vignotto E., Engelke S. & Zscheischler J. (2021)
Clustering bivariate dependencies of compound precipitation and wind extremes over Great Britain and Ireland.
Weather and Climate Extremes, 32.
Zscheischler J., Naveau P., Martius O., Engelke S. & Raible, C. (2021)
Evaluating the dependence structure of compound precipitation and wind speed extremes.
Earth System Dynamics, 12, 1-16.
Vignotto E. & Engelke S. (2020)
Extreme value theory for anomaly detection - the GPD classifier.
Extremes, 23, 501-520. [arxiv]
Engelke S., Opitz T. & Wadsworth J. (2019).
Extremal dependence of random scale constructions.
Extremes, 22: 623-666. [arxiv , shiny]
Engelke S., de Fondeville R. & Oesting M. (2019).
Extremal behavior of aggregated data with an application to downscaling.
Biometrika, 106: 127-144. [arxiv]
Le P.D., Davison A.C., Engelke S., Leonard M. & Westra S. (2018).
Dependence properties of spatial rainfall extremes and areal reduction factor.
Journal of Hydrology , 565: 711-719.
Asadi P., Engelke S. & Davison A.C. (2018).
Optimal regionalization of extreme value distributions for flood estimation.
Journal of Hydrology, 556: 182-193. [arxiv]
Dombry C., Engelke S. & Oesting M. (2017).
Bayesian inference for multivariate extreme value distributions.
Electronic Journal of Statistics, 11: 4813-4844. [arxiv]
Engelke S. & Ivanovs J. (2017).
Robust bounds in multivariate extremes.
Annals of Applied Probability, 27: 3706-3734. [arxiv]
Best presentation CFENetwork - CMStatistics & CRoNoS Award
Dębicki, K., Engelke S. & Hashorva, E. (2017).
Generalized Pickands constants and stationary max-stable processes.
Extremes, 19: 1-6. [arxiv]
Dombry C., Engelke S. & Oesting M. (2016).
Exact simulation of max-stable processes.
Biometrika, 103: 303-317. [arxiv, code]
Engelke S. & Ivanovs J. (2016).
A Lévy-derived process seen from its supremum and max-stable processes.
Electronic Journal of Probability, 21: paper no. 14. [arxiv]
Engelke S. & Kabluchko Z. (2016).
A characterization of the normal distribution using stationary max-stable processes.
Extremes, 20: 493-517. [arxiv]
Engelke S., Kabluchko Z. & Schlather M. (2015).
Maxima of independent, non-identically distributed Gaussian vectors.
Bernoulli, 21: 38-61. [arxiv]
Das B., Engelke S. & Hashorva E. (2015).
Extremal behavior of squared Bessel processes attracted by the Brown-Resnick process.
Stochastic Processes and their Applications, 125: 780-796. [arxiv]
Engelke S., Malinowski A., Oesting M. & Schlather M. (2014).
Statistical inference for max-stable processes by conditioning on extreme events.
Advances in Applied Probability, 46: 478-495. [arxiv]
Engelke S. & Woerner J.H.C. (2013).
A unifying approach to fractional Lévy processes.
Stochastics and Dynamics, 13: DOI: 10.1142/S021949371250017.
Engelke S., Kabluchko Z. & Schlather M. (2011).
An equivalent representation of the Brown-Resnick process.
Statistics & Probability Letters, 81: 1150-1154.
Engelke S. & Schlather M. (2011).
Book review: Environmental and Ecological Statistics with S. Song S. Qian (2010). Boca Raton, FL, USA: Chapman & Hall/CRC.
Biometrical Journal, 53: 867.