Tim Roith – Department Mathematik

Tim Roith

Promotionsstudent

Lehrstuhl für Angewandte Mathematik (Modellierung und Numerik)
Mathematics of Data Science

Telefon: +49 9131 85-67209

Publikationen

2023

Kabri S., Roith T., Tenbrinck D., Burger M.:
Resolution-Invariant Image Classification Based on Fourier Neural Operators
International Conference on Scale Space and Variational Methods in Computer Vision (Santa Margherita di Pula, 23-05-2023 - 25-05-2023)
In: Scale Space and Variational Methods in Computer Vision 2023
DOI: 10.1007/978-3-031-31975-4_18
BibTeX: Download

2022

Bungert L., Calder J., Roith T.:
Uniform convergence rates for Lipschitz learning on graphs
In: IMA Journal of Numerical Analysis (2022)
ISSN: 0272-4979
DOI: 10.1093/imanum/drac048
BibTeX: Download
Bungert L., Roith T., Tenbrinck D., Burger M.:
A Bregman Learning Framework for Sparse Neural Networks
In: Journal of Machine Learning Research (2022)
ISSN: 1532-4435
Open Access: https://www.jmlr.org/papers/v23/21-0545.html
BibTeX: Download
Roith T., Bungert L.:
Continuum Limit of Lipschitz Learning on Graphs
In: Foundations of Computational Mathematics (2022)
ISSN: 1615-3375
DOI: 10.1007/s10208-022-09557-9
BibTeX: Download

2021

Bungert L., Raab R., Roith T., Schwinn L., Tenbrinck D.:
CLIP: Cheap Lipschitz Training of Neural Networks
International Conference on Scale Space and Variational Methods in Computer Vision
In: Abderrahim Elmoataz, Jalal Fadili, Yvain Quéau, Julien Rabin, Loïc Simon (Hrsg.): SSVM 2021: Scale Space and Variational Methods in Computer Vision, Cham: 2021
DOI: 10.1007/978-3-030-75549-2_25
URL: https://arxiv.org/abs/2103.12531
BibTeX: Download