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Tim Roith
Tim Roith
PhD Student, Deutsches Elektronen-Synchrotron DESY
Verified email at desy.de - Homepage
Title
Cited by
Cited by
Year
CLIP: Cheap Lipschitz training of neural networks
L Bungert, R Raab, T Roith, L Schwinn, D Tenbrinck
International Conference on Scale Space and Variational Methods in Computer …, 2021
302021
Continuum limit of Lipschitz learning on graphs
T Roith, L Bungert
Foundations of Computational Mathematics 23 (2), 393-431, 2023
202023
A Bregman learning framework for sparse neural networks
L Bungert, T Roith, D Tenbrinck, M Burger
Journal of Machine Learning Research 23 (192), 1-43, 2022
182022
Uniform convergence rates for Lipschitz learning on graphs
L Bungert, J Calder, T Roith
IMA Journal of Numerical Analysis 43 (4), 2445-2495, 2023
162023
Polarized consensus-based dynamics for optimization and sampling
L Bungert, T Roith, P Wacker
arXiv preprint arXiv:2211.05238, 2022
92022
Ratio convergence rates for Euclidean first-passage percolation: applications to the graph infinity Laplacian
L Bungert, J Calder, T Roith
arXiv preprint arXiv:2210.09023, 2022
72022
Neural architecture search via Bregman iterations
L Bungert, T Roith, D Tenbrinck, M Burger
arXiv preprint arXiv:2106.02479, 2021
72021
Resolution-invariant image classification based on fourier neural operators
S Kabri, T Roith, D Tenbrinck, M Burger
International Conference on Scale Space and Variational Methods in Computer …, 2023
42023
CBX: Python and Julia packages for consensus-based interacting particle methods
R Bailo, A Barbaro, SN Gomes, K Riedl, T Roith, C Totzeck, U Vaes
arXiv preprint arXiv:2403.14470, 2024
2024
Consistency, Robustness and Sparsity for Learning Algorithms
T Roith
Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU …, 2024
2024
Learning a Sparse Representation of Barron Functions with the Inverse Scale Space Flow
TJ Heeringa, T Roith, C Brune, M Burger
arXiv preprint arXiv:2312.02671, 2023
2023
Adversarial Flows
L Weigand, T Roith, M Burger
2023
Lipschitz Learning using Graphs and Neural Networks
L Bungert, T Roith, D Tenbrinck
2021
TimRoith/BregmanLearning📈 BregmanLearning
L Bungert, T Roith, D Tenbrinck, M Burger
2021
L-Infinity Variational Problems on Graphs: Applications and Continuum Limits
L Bungert, T Roith
2020
Convergence Rates for Lipschitz Learning on Very Sparse Graphs
L Bungert, J Calder, T Roith
Einführung in die Numerik
M Burger, D Tenbrinck, T Roith
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Articles 1–17