Publications

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Hobolth, A. & Jensen, J. L. (2011). Summary statistics for endpoint-conditioned continuous-time Markov chains. Journal of Applied Probability, 48(4), 911-924. https://doi.org/10.1239/jap/1324046009

Hobolth, A. (2012). Ancestral population genomics. In M. Anisimova (Ed.), Evolutionary Genomics: Statistical and Computational Methods (Vol. 856, pp. 293-313). Springer.

Hobolth, A. & Jensen, E. B. V. (2000). Modelling stochastic chances in curve shape, with an application to cancer diagnostics. Advances in Applied Probability, 32(2), 344-362. https://doi.org/10.1239/aap/1013540167

Hobolth, A. & Jensen, J. L. (2014). Markovian approximation to the finite loci coalescent with recombination along multiple sequences. Theoretical Population Biology, 98, 48-58. https://doi.org/10.1016/j.tpb.2014.01.002

Hobolth, A. & Jeff, T. (2014). Sampling and summary statistics of endpoint-conditioned paths in DNA sequence evolution. In M.-H. Chen, L. Kuo & P. O. Lewis (Eds.), Bayesian Phylogenetics: Methods, Algorithms, and Applications (1 ed., Vol. 1). CRC Press.

Hobolth, A. & Siren, J. (2016). The multivariate Wright–Fisher process with mutation: Moment-based analysis and inference using a hierarchical Beta model. Theoretical Population Biology, 108, 36-50. https://doi.org/10.1016/j.tpb.2015.11.001

Hobolth, A., Siri-Jegousse, A. & Bladt, M. (2019). Phase-type distributions in population genetics. Theoretical Population Biology, 127, 16-32. https://doi.org/10.1016/j.tpb.2019.02.001

Hobolth, A., Guo, Q., Kousholt, A. & Jensen, J. L. (2020). A Unifying Framework and Comparison of Algorithms for Non-negative Matrix Factorisation. International Statistical Review, 88(1), 29-53. https://doi.org/10.1111/insr.12331

Hobolth, A., Bladt, M. & Andersen, L. N. (2021). Multivariate phase-type theory for the site frequency spectrum. Journal of Mathematical Biology, 83(6-7), Article 63. https://doi.org/10.1007/s00285-021-01689-w

Hobolth, A. & Wiuf, C. (2024). Maximum likelihood estimation and natural pairwise estimating equations are identical for three sequences and a symmetric 2-state substitution model. Theoretical Population Biology, 156, 1-4. https://doi.org/10.1016/j.tpb.2023.12.004

Hobolth, A., Rivas-González, I., Bladt, M. & Futschik, A. (2024). Phase-type distributions in mathematical population genetics: An emerging framework. Theoretical Population Biology, 157, 14-32. https://doi.org/10.1016/j.tpb.2024.03.001

Hobolth, A., Boitard, S., Futschik, A. & Leblois, R. (2025). A matrix-analytical sampling formula for time-homogeneous coalescent processes under the infinite sites mutation model. Theoretical Population Biology, 163, 62-79. https://doi.org/10.1016/j.tpb.2025.03.002

Hobolth, A. (2002). Statistical shape analysis of featureless objects. Department of Mathematical Sciences, Aarhus University.

Hirsch, C., Holmes, M. & Kleptsyn, V. (2021). Absence of WARM percolation in the very strong reinforcement regime. Annals of Applied Probability, 31(1), 199-217. https://doi.org/10.1214/20-AAP1587

Hirsch, C. (2020). On the decomposability of mod 2 cohomological invariants of Weyl groups. Commentarii Mathematici Helvetici, 95(4), 765-809. https://doi.org/10.4171/CMH/503

Hirsch, C., Bharti, A., Pedersen, T. & Waagepetersen, R. (2021). Maximum Likelihood Calibration of Stochastic Multipath Radio Channel Models. IEEE Transactions on Antennas and Propagation, 69(7), 4058-4069. Article 9298915. https://doi.org/10.1109/TAP.2020.3044379

Hirsch, C., Moka, S. B., Taimre, T. & Kroese, D. P. (2022). Rare Events in Random Geometric Graphs. Methodology and Computing in Applied Probability, 24(3), 1367-1383. https://doi.org/10.1007/s11009-021-09857-7

Hirsch, C., Jahnel, B. & Cali, E. (2019). Continuum percolation for Cox point processes. Stochastic processes and their applications, 129(10), 3941-3966. https://doi.org/10.1016/j.spa.2018.11.002

Hirsch, C., Neuhäuser, D., Gloaguen, C. & Schmidt, V. (2015). First passage percolation on random geometric graphs and an application to shortest-path trees. Advances in Applied Probability, 47(2), 328-354.

Hirsch, C., Jahnel, B., Keeler, P. & Patterson, R. (2018). Large deviations in relay-augmented wireless networks. Queueing Systems, 88(3-4), 349-387. https://doi.org/10.1007/s11134-017-9555-9

Hirsch, C. (2017). From heavy-tailed Boolean models to scale-free Gilbert graphs. Brazilian Journal of Probability and Statistics, 31(1), 111-143.

Hirsch, C., Neuhäuser, D. & Schmidt, V. (2016). Moderate deviations for shortest-path lengths on random segment processes. ESAIM: Probability and Statistics, 20, 261-292.

Hirsch, C., Neuhaeuser, D. & Schmidt, V. (2013). Connectivity of random geometric graphs related to minimal spanning forests. Advances in Applied Probability, 45(1), 20-36.

Hirsch, C., Jahnel, B., Keeler, P. & Patterson, R. IA. (2016). Large deviation principles for connectable receivers in wireless networks. Advances in Applied Probability, 48(4), 1061-1094.

Hirsch, C., Neuhäuser, D., Gloaguen, C. & Schmidt, V. (2015). Asymptotic properties of Euclidean shortest-path trees in random geometric graphs. Statistics probability letters, 107, 122-130.

Hirsch, C., Cali, E., Patterson, R., En-Najjary, T., Gafur, N. & Jahnel, B. (2018). Percolation for D2D networks on street systems. In 2018 16th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, WiOpt 2018 (Vol. 16) https://doi.org/10.23919/WIOPT.2018.8362866

Hirsch, C., Brereton, T. & Schmidt, V. (2017). Percolation and convergence properties of graphs related to minimal spanning forests. Electronic Journal of Probability, 22, 1-21.

Hirsch, C. (2016). Bounded-hop percolation and wireless communication. Journal of Applied Probability, 53(3), 833-845.

Hirsch, C. (2015). A Harris-Kesten theorem for confetti percolation. Random Structures Algorithms, 47(2), 361-385.

Hirsch, C., Jahnel, B., Keeler, P. & Patterson, R. IA. (2017). Traffic flow densities in large transport networks. Advances in Applied Probability, 49(4), 1091-1115.

Hirsch, C., Delaney, G. & Schmidt, V. (2015). Stationary Apollonian Packings. Journal of Statistical Physics, 161(1), 35-72.

Hirsch, C. (2016). On the absence of percolation in a line-segment based lilypond model. In Annales de l'Institut Henri Poincaré, Probabilités et Statistiques (Vol. 52, pp. 127-145)

Hirsch, C. & Last, G. (2018). On maximal hard-core thinnings of stationary particle processes. Journal of Statistical Physics, 170(3), 554-583. https://doi.org/10.1007/s10955-017-1943-3

Hirsch, C., Jahnel, B. & Cali, E. (2022). Percolation and connection times in multi-scale dynamic networks. Stochastic Processes and Their Applications, 151, 490-518. https://doi.org/10.1016/j.spa.2022.06.008

Hirsch, C., Jahnel, B. & Muirhead, S. (2022). Sharp phase transition for Cox percolation. Electronic Communications in Probability, 27, 1-13. https://doi.org/10.1214/22-ECP487

Hirsch, C., Neumann, M. & Schmidt, V. (2023). Asymptotic properties of one-layer artificial neural networks with sparse connectivity. Statistics & Probability Letters, 193, Article 109698. https://doi.org/10.1016/j.spl.2022.109698

Hirsch, C., Jahnel, B. & Cali, E. (2023). Connection intervals in multi-scale infrastructure-augmented dynamic networks. Stochastic Models, 39(4), 851-877. https://doi.org/10.1080/15326349.2023.2184832

Hirsch, C. P., Otto, M., Owada, T. & Thäle, C. (2023). LARGE DEVIATIONS FOR THE VOLUME OF HYPERBOLIC k-NEAREST NEIGHBOR BALLS.

Hirsch, C., Holmes, M. & Kleptsyn, V. (2023). Infinite WARM graphs III: Strong reinforcement regime. Nonlinearity, 36(6), 3013-3042. https://doi.org/10.1088/1361-6544/acc9a0

Hirsch, C. P., Otto, M. & Svane, A. M. (2024). NORMAL APPROXIMATION FOR GIBBS PROCESSES VIA DISAGREEMENT COUPLINGS. https://doi.org/10.1214/25-EJP1351

Hirsch, C. & Willhalm, D. (2024). Lower large deviations for geometric functionals in sparse, critical and dense regimes. Alea (Rio de Janeiro), 21(2), 923-962. https://doi.org/10.30757/ALEA.V21-38

Hirsch, C. & Willhalm, D. (2025). Large deviations of one-hidden-layer neural networks. Stochastics and Dynamics, 24(8), Article 2550002. https://doi.org/10.1142/S0219493725500029

Hirsch, C., Jahnel, B., Jhawar, S. K. & Juhasz, P. (2025). Poisson approximation of fixed-degree nodes in weighted random connection models. Stochastic Processes and Their Applications, 183, Article 104593. https://doi.org/10.1016/j.spa.2025.104593

Hirsch, C. & Valesin, D. (2025). Face and cycle percolation. Journal of Applied and Computational Topology, 9(1), Article 6. https://doi.org/10.1007/s41468-025-00202-2

Hirsch, C. & Petráková, M. (2025). Large-Deviation Analysis for Canonical Gibbs Measures. Journal of Statistical Physics, 192(5), Article 71. https://doi.org/10.1007/s10955-025-03451-8

Hirsch, C. & Juhasz, P. (2025). On the Topology of Higher-order Age-dependent Random Connection Models. Methodology and Computing in Applied Probability, 27(2), Article 44. https://doi.org/10.1007/s11009-025-10173-7

Hirsch, C. P., Jahnel, B. & Juhász, P. (2025). Functional limit theorems for edge counts in dynamic random connection hypergraphs. https://arxiv.org/pdf/2507.16270

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., Otto, M., Owada, T. & Thäle, C. (2025). Large deviations for the volume of hyperbolic k-nearest neighbor balls. Annales de l'institut Henri Poincare (B) Probability and Statistics, 61(2), 1443-1457. https://doi.org/10.1214/23-AIHP1458

Hirsch, C., Lundbye, N. N. & Otto, M. (2026). Poisson approximation of large-lifetime cycles. Extremes. Advance online publication. https://doi.org/10.1007/s10687-026-00526-x

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Revised 03.03.2026

Lars Madsen