Department of Mathematics

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2026

Working Paper

Labouriau, R. (2026). Distributional Statistical Models: Weak Moments, Cumulants, and a Central Limit Theorem.
Labouriau, R. (2026). From Coefficients to Distributions: De~Moivre and the Operational View of Probability.
Labouriau, R. (2026). Markov Properties of $k$-Record Processes via Order Statistics.
Labouriau, R. (2026). Notes on Transversality and Statistical Degeneracies in Distributional Models.
Labouriau, R. (2026). Transversality and Geometric Regularisation in Distributional Statistical Models.
Labouriau, R. (2026). Weak Information Geometry: Riemannian Structures from Distributional Inference Functions and Stein Discrepancies.
Labouriau, R. (2026). Weak Moment Methods for Statistical Inference: with an Application to Robust Estimation.
Kutta, T., Dörnemann, N. & Kokoszka, P. (2026). Does PCA Work for Rough Functional Data?
Holk, A., Strauch, C. & Trottner, L. (2026). Reflected diffusion models adapt to low-dimensional data.
Holk, A., Strauch, C. & Trottner, L. (2026). Statistical guarantees for denoising reflected diffusion models.
Exarchakos, G., van der Hofstad, R., Nagy, O. & Pandey, M. (2026). Bringing order to network centrality measures. (pp. 1-24). ArXiv. https://arxiv.org/abs/2601.16236
Baudoin, F. & Yang, G. (2026). Sub-Laplacian generalized curvature dimension inequalities on Riemannian foliations.
Bastian, P., Tieplova, D., Dörnemann, N. & Kutta, T. (2026). Change Point Detection and Localization in High-Dimensional Time Series.

2026

Book anthology

Jensen, J. L., Mortensen, P. B. & Serritzlew, S. (2026). Understanding Policy Changes: The Mixture Model of Politics. Oxford University Press. https://doi.org/10.1093/9780197900413.001.0001

2026

Contribution to journal

Sendrowski, J. & Hobolth, A. (2026). PhaseGen: exact solutions for time-inhomogeneous multivariate coalescent distributions under diverse demographies. Genetics, 232(1), Article iyaf135. https://doi.org/10.1093/genetics/iyaf135
Ramos-Docampo, M. A., Duan, C., Wang, N., Pandey, M., de Dios Andres, P., Hirsch, C. & Städler, B. (2026). Modeling Active Particle Motion from Fluorescence Correlation Spectroscopy Data. Analytical Chemistry, 98(31), 22781-22791. https://doi.org/10.1021/acs.analchem.6c01438
Pérez-Abreu, V. & Ørnsen, S. T. (2026). On Ole E. Barndorff-Nielsen’s contributions to classical and free infinite divisibility and Lévy processes. Bernoulli, 32(1), 5-23. https://doi.org/10.3150/25-BEJ1896
Ozkan, R. (2026). Geometric Deep Learning: A Bibliometric Analysis of Research Evolution and Emerging Directions. IEEE Access, 14, 124642-124662. https://doi.org/10.1109/ACCESS.2026.3723132
Nagy, O., Pandey, M., Exarchakos, G., Bentum, M. & van der Hofstad, R. (2026). Communication protocol for a satellite-swarm interferometer for low-frequency radio astronomy. Acta Astronautica, 246, 821-831. https://doi.org/10.1016/j.actaastro.2026.04.004
Moka, S., Hirsch, C., Schmidt, V. & Kroese, D. (2026). Efficient Rare-Event Simulation for Random Geometric Graphs via Importance Sampling. Methodology and Computing in Applied Probability, 28(2), Article 44. https://doi.org/10.1007/s11009-026-10273-y
Hirsch, C. & Owada, T. (2026). Limit theorems under heavy-tailed scenario in the age-dependent random connection models. Stochastic Processes and Their Applications, 192, Article 104815. https://doi.org/10.1016/j.spa.2025.104815
Hirsch, C., Lundbye, N. N. & Otto, M. (2026). Poisson approximation of large-lifetime cycles. Extremes, 29(3), 495-559. https://doi.org/10.1007/s10687-026-00526-x
Gao, J. & Yang, M. (2026). Hölder regularity of harmonic functions on metric measure spaces. Advances in Mathematics, 488, Article 110797. https://doi.org/10.1016/j.aim.2026.110797
Dörnemann, N. T. & Dette, H. (2026). A CLT for the difference of eigenvalue statistics of sample covariance matrices. Bernoulli, 32(1), 615-637. https://doi.org/10.3150/25-BEJ1872
Dörnemann, N. & Paul, D. S. (2026). Detecting spectral breaks in spiked covariance models. Bernoulli, 32(2), 1243-1266. https://doi.org/10.3150/25-BEJ1900
Dörnemann, N., Fleermann, M. & Heiny, J. (2026). Ties, tails and spectra: On rank-based dependency measures in high dimensions. Stochastic processes and their applications, 201, Article 105055. https://doi.org/10.1016/j.spa.2026.105055
Dörnemann, N. (2026). Two-sample covariance inference in high-dimensional elliptical models. Electronic Journal of Statistics, 20(1), 633-666. https://doi.org/10.1214/26-EJS2499
Coll Macià, M., Skov, L., Bæk, Z. E. D. & Hobolth, A. (2026). Enhancement of hidden Markov model analyses for improved inference of archaic introgression in modern humans. Molecular Biology and Evolution, 43(6), Article msag134. https://doi.org/10.1093/molbev/msag134
Chen, H. & Lee, C. Y. (2026). Propagation of singularities for the damped stochastic Klein-Gordon equation. Stochastics and Partial Differential Equations: Analysis and Computations. Advance online publication. https://doi.org/10.1007/s40072-026-00433-z
Chen, A. & Yu, Z. (2026). Spectral Bounds and Heat Kernel Upper Estimates for Dirichlet Forms. Mathematische Nachrichten, 299(9), 2566-2589. Article e70207. https://doi.org/10.1002/mana.70207
Brun, M., Hirsch, C., Juhász, P. & Otto, M. (2026). Random connection hypergraphs. Stochastic Models, 42(3), 345-387. https://doi.org/10.1080/15326349.2026.2651174
Bendikov, A., Chen, L. & Saloff-Coste, L. (2026). Riesz Transforms, Function Spaces, and Their Applications on Infinite Dimensional Compact Groups. Potential Analysis, 64(4), Article 60. https://doi.org/10.1007/s11118-026-10288-7
Baudoin, F., Gordina, M. & Sarkar, R. (2026). Dimension-Independent Functional Inequalities by Tensorization and Projection Arguments. Mathematische Nachrichten, 299(7), 1665-1691. https://doi.org/10.1002/mana.70164
Baudoin, F., Chen, L., Huang, C. H., Ouyang, C., Tindel, S. & Wang, J. (2026). Parabolic Anderson model in bounded domains of recurrent metric measure spaces. Transactions of the American Mathematical Society, 379(3), 1799-1851. https://doi.org/10.1090/tran/9540
Baudoin, F., Kuijper, T. & Wang, J. (2026). Quaternionic Stochastic Areas on Quaternionic Full Flag Manifolds and Applications. Journal of Theoretical Probability, 39(3), Article 52. https://doi.org/10.1007/s10959-026-01514-4
Baudoin, F. (2026). Sub-Laplacian comparison theorems on Riemannian foliations with minimal leaves and applications. Communications on Pure and Applied Analysis, 32, 192-214. https://doi.org/10.3934/cpaa.2026035
Bæk, Z. E. D., Macià, M. C., Skov, L. & Hobolth, A. (2026). Advanced Posterior Analyses of Hidden Markov Models: Finite Markov Chain Imbedding and Hybrid Decoding. Scandinavian journal of statistics. Advance online publication. https://doi.org/10.1111/sjos.70088
Asmussen, S. (2026). On Erlangization and Extrapolation, with Applications to Financial Regime-Switching Lévy Models. Methodology and Computing in Applied Probability, 28(1), Article 19. https://doi.org/10.1007/s11009-025-10234-x
Andreis, L., Bassetti, F. & Hirsch, C. (2026). LDP for the covariance process in fully connected Gaussian neural networks. Electronic Journal of Probability, 31, Article 22. https://doi.org/10.1214/26-EJP1477
Agergaard, T. E., Nielsen, K. H., Labouriau, R. & Fage-Butler, A. (2026). Exploring Trust and Literacy in Engagement with Generative AI and Science Information Behavior. Media and Communication, 14, Article 11357. https://doi.org/10.17645/mac.11357
Dare, E. (2025). Corrigendum to “Stereologically adapted Crofton formulae for tensor valuations” [Adv. Appl. Math. 160 (2024) 102754] (Advances in Applied Mathematics (2024) 160, (S0196885824000861), (10.1016/j.aam.2024.102754)). Advances in Applied Mathematics, 171, Article 102937. https://doi.org/10.1016/j.aam.2025.102937

2025

Working Paper

Lam, T., Dörnemann, N. & Dette, H. (2025). A New Two-Sample Test for Covariance Matrices in High Dimensions: U-Statistics Meet Leading Eigenvalues.
Kuijper, T. (2025). Brownian motion and stochastic areas on complex partial flag manifolds with blocks of equal size.
Jain, S., de Freitas, B. N., Basse-OConnor, A., Iosifidis, A. & Pauwels, R. (2025). PanoDiff-SR: Synthesizing Dental Panoramic Radiographs using Diffusion and Super-resolution.
Dörnemann, N., Kokoszka, P., Kutta, T. & Lee, S. (2025). Monitoring for a Phase Transition in a Time Series of Wigner Matrices.
Dörnemann, N., Fleermann, M. & Heiny, J. (2025). Ties, Tails and Spectra: On Rank-Based Dependency Measures in High Dimensions.
Dörnemann, N. & Lopes, M. E. (2025). Tracy-Widom, Gaussian, and Bootstrap: Approximations for Leading Eigenvalues in High-Dimensional PCA.
Dörnemann, N. (2025). Two-Sample Covariance Inference in High-Dimensional Elliptical Models.
Baudoin, F., Kuijper, T. & Wang, J. (2025). Quaternionic stochastic areas on quaternionic full flag manifolds and applications.
Baudoin, F., Chen, L., Huang, C.-H., Ouyang, C., Tindel, S. & Wang, J. (2025). Weighted Besov spaces on Heisenberg groups and applications to the Parabolic Anderson model. ArXiv. https://doi.org/10.48550/arXiv.2501.04593

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Revised 10.06.2026
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Lars Madsen