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Tim Roith
Tim Roith
Postdoc, Deutsches Elektronen-Synchrotron DESY
E-mailová adresa ověřena na: desy.de - Domovská stránka
Název
Citace
Citace
Rok
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
412021
Continuum limit of Lipschitz learning on graphs
T Roith, L Bungert
Foundations of Computational Mathematics 23 (2), 393-431, 2023
332023
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
262022
Uniform convergence rates for Lipschitz learning on graphs
L Bungert, J Calder, T Roith
IMA Journal of Numerical Analysis 43 (4), 2445-2495, 2023
252023
Polarized consensus-based dynamics for optimization and sampling
L Bungert, T Roith, P Wacker
Mathematical Programming, 1-31, 2024
232024
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
112024
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
102023
Ratio convergence rates for Euclidean first-passage percolation: applications to the graph infinity Laplacian
L Bungert, J Calder, T Roith
The Annals of Applied Probability 34 (4), 3870-3910, 2024
92024
Neural architecture search via Bregman iterations
L Bungert, T Roith, D Tenbrinck, M Burger
arXiv preprint arXiv:2106.02479, 2021
82021
Analysis of mean-field models arising from self-attention dynamics in transformer architectures with layer normalization
M Burger, S Kabri, Y Korolev, T Roith, L Weigand
arXiv preprint arXiv:2501.03096, 2025
12025
Learning a Sparse Representation of Barron Functions with the Inverse Scale Space Flow
TJ Heeringa, T Roith, C Brune, M Burger
12023
MirrorCBO: A consensus-based optimization method in the spirit of mirror descent
L Bungert, F Hoffmann, DY Kim, T Roith
arXiv preprint arXiv:2501.12189, 2025
2025
Learning in Image Reconstruction: A Cautionary Tale
M Burger, T Roith
Collections 57 (08), 2024
2024
Adversarial flows: A gradient flow characterization of adversarial attacks
L Weigand, T Roith, M Burger
arXiv preprint arXiv:2406.05376, 2024
2024
Polarized consensus-based dynamics for optimization and sampling
P Wacker, L Bungert, T Roith
2024
Consistency, Robustness and Sparsity for Learning Algorithms
T Roith
Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU …, 2024
2024
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
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Články 1–20