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Thaddäus Wiedemer
Thaddäus Wiedemer
Max Planck Institute for Intelligent Systems & University of Tübingen
Verified email at uni-tuebingen.de
Title
Cited by
Cited by
Year
Interpretable and fine-grained visual explanations for convolutional neural networks
J Wagner, JM Kohler, T Gindele, L Hetzel, JT Wiedemer, S Behnke
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019
1592019
Compositional generalization from first principles
T Wiedemer, P Mayilvahanan, M Bethge, W Brendel
Advances in Neural Information Processing Systems 36, 2024
72024
Few-shot supervised prototype alignment for pedestrian detection on fisheye images
T Wiedemer, S Wolf, A Schumann, K Ma, J Beyerer
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022
72022
Does CLIP's Generalization Performance Mainly Stem from High Train-Test Similarity?
P Mayilvahanan, T Wiedemer, E Rusak, M Bethge, W Brendel
arXiv preprint arXiv:2310.09562, 2023
32023
Provable Compositional Generalization for Object-Centric Learning
T Wiedemer, J Brady, A Panfilov, A Juhos, M Bethge, W Brendel
arXiv preprint arXiv:2310.05327, 2023
2023
Method and device for ascertaining an explanation map
J Wagner, T Gindele, JM Koehler, JT Wiedemer, L Hetzel
US Patent 11,645,828, 2023
2023
Scale Learning in Scale-Equivariant Convolutional Networks
M Basting, RJ Bruintjes, T Wiedemer, M Kümmerer, M Bethge, ...
2023
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