Publications/Preprints

Realising atomless laws as distance distributions on metric measure spaces

Jointly with: Christoph Thäle

Published as arXiv preprint, 2026

Citation: C. Thäle and P. Tuchel (2026). "Realising atomless laws as distance distributions on metric measure spaces." arXiv preprint. arXiv:2608.28330. https://arxiv.org/abs/2608.28330

Mod-phi convergence for random variables with cyclotomic generating functions

Jointly with: Christoph Thäle

Published as arXiv preprint, 2026

Citation: C. Thäle and P. Tuchel (2026). "Mod-phi convergence for random variables with cyclotomic generating functions." arXiv preprint. arXiv:2608.14143. https://arxiv.org/abs/2608.14143

Benchmarks in Leipzig

Jointly with: Andrei Balakin, Miklós Bóna, Marie-Charlotte Brandenburg, Clara Briand, Veronica Calvo Cortes, Shelby Cox, Jesus A. De Loera, Danai Deligeorgaki, Hannah Friedman, Tim Gehrunger, Chiara Giardino, Stephen Griffeth, Baran Hashemi, Elena Hoster, Alexander Ivanov, Nupur Jain, Aryaman Jal, Leonie Kayser, Joris Koefler, Kevin Kühn, Mario Kummer, Felix Lotter, René Marczinzik, Victor S. Miller, Alejandro Morales, Greta Panova, Gianni Petrella, Nathan Pflueger, Lakshmi Ramesh, Nikolas Rieke, Carlos Rodriguez, Andrea Rosana, Flavio Salizzoni, Otto T.P. Schmidt, Sven Ulf Schmitz, Lina Maria Simbaqueba Marin, Luca Sodomaco, Christian Stump, Bernd Sturmfels, Alexander Taveira Blomenhofer, Simon Telen, Emil Verkama, Carl Felix Waller, Julian Weigert, Annette Werner, Nathan Williams, and Claudius Zibrowius

Published as arXiv preprint, 2026

Citation: A. Balakin et al. (2026). "Benchmarks in Leipzig." arXiv preprint. arXiv:2606.05818. https://arxiv.org/abs/2606.05818

Large deviations for sums of multivariate stretched-exponential random variables: the few-big-jumps principle

Jointly with: Nina Gantert and Joscha Prochno

Published as arXiv preprint, 2026

Citation: N. Gantert, J. Prochno, and P. Tuchel (2026). "Large deviations for sums of multivariate stretched-exponential random variables: the few-big-jumps principle." arXiv preprint. arXiv:2602.01168. https://arxiv.org/abs/2602.01168

On the Universal Representation Property of Spiking Neural Networks

Jointly with: Shayan Hundrieser, Insung Kong, and Johannes Schmidt-Hieber

Published as arXiv preprint, 2025

Citation: S. Hundrieser, P. Tuchel, I. Kong, and J. Schmidt-Hieber (2025). "On the Universal Representation Property of Spiking Neural Networks." arXiv preprint. arXiv:2512.16872. https://arxiv.org/abs/2512.16872

Large and Moderate Deviations for Entries of Orthogonal Matrices and the Stiefel Manifold

Published as arXiv preprint, 2025

Citation: P. Tuchel (2025). "Large and Moderate Deviations for Entries of Orthogonal Matrices and the Stiefel Manifold." preprint. https://arxiv.org/abs/2509.24538

Limit Theorems for the Volume of Random Projections and Sections of ℓ_p^N-balls

Jointly with: Joscha Prochno and Christoph Thäle

Published as arXiv preprint, 2024

Citation: J. Prochno, and C. Thäle, P. Tuchel (2024). "Limit Theorems for the Volume of Random Projections and Sections of ℓNp -balls." arXiv preprint. arXiv:2412.16054. https://arxiv.org/abs/2412.16054

A Continual and Incremental Learning Approach for TinyML On-device Training Using Dataset Distillation and Model Size Adaption

Jointly with: Marcus Rüb, Axel Sikora, and Daniel Mueller-Gritschneder

Published in Proceedings of the 2024 IEEE 7th International Conference on Industrial Cyber-Physical Systems (ICPS), 2024

Citation: M. Rüb, P. Tuchel, A. Sikora, and D. Mueller-Gritschneder (2024). "A Continual and Incremental Learning Approach for TinyML On-device Training Using Dataset Distillation and Model Size Adaption." Proceedings of the 2024 IEEE 7th International Conference on Industrial Cyber-Physical Systems (ICPS), pp. 1-8. https://doi.org/10.1109/ICPS59941.2024.10639989