Publications/Preprints

On the Universal Representation Property of Spiking Neural Networks

Jointly with: 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 in 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: 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: 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