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2020 – today
- 2024
[c6]Prasanna Mayilvahanan, Thaddäus Wiedemer, Evgenia Rusak, Matthias Bethge, Wieland Brendel:
Does CLIP's generalization performance mainly stem from high train-test similarity? ICLR 2024- [c5]Thaddäus Wiedemer, Jack Brady, Alexander Panfilov, Attila Juhos, Matthias Bethge, Wieland Brendel:
Provable Compositional Generalization for Object-Centric Learning. ICLR 2024 - [c4]Mark Basting, Robert-Jan Bruintjes, Thaddäus Wiedemer, Matthias Kümmerer, Matthias Bethge, Jan van Gemert:
Scale Learning in Scale-Equivariant Convolutional Networks. VISIGRAPP (2): VISAPP 2024: 567-574 - 2023
- [c3]Thaddäus Wiedemer, Prasanna Mayilvahanan, Matthias Bethge, Wieland Brendel:
Compositional Generalization from First Principles. NeurIPS 2023 - [i4]Thaddäus Wiedemer
, Prasanna Mayilvahanan, Matthias Bethge, Wieland Brendel:
Compositional Generalization from First Principles. CoRR abs/2307.05596 (2023) - [i3]Thaddäus Wiedemer, Jack Brady, Alexander Panfilov, Attila Juhos, Matthias Bethge, Wieland Brendel:
Provable Compositional Generalization for Object-Centric Learning. CoRR abs/2310.05327 (2023) - [i2]Prasanna Mayilvahanan, Thaddäus Wiedemer, Evgenia Rusak, Matthias Bethge, Wieland Brendel:
Does CLIP's Generalization Performance Mainly Stem from High Train-Test Similarity? CoRR abs/2310.09562 (2023) - 2022
- [c2]Thaddäus Wiedemer, Stefan Wolf, Arne Schumann, Kaisheng Ma, Jürgen Beyerer:
Few-Shot Supervised Prototype Alignment for Pedestrian Detection on Fisheye Images. CVPR Workshops 2022: 4141-4152
2010 – 2019
- 2019
- [c1]Jörg Wagner, Jan Mathias Köhler, Tobias Gindele, Leon Hetzel, Jakob Thaddäus Wiedemer, Sven Behnke:
Interpretable and Fine-Grained Visual Explanations for Convolutional Neural Networks. CVPR 2019: 9097-9107 - [i1]Jörg Wagner, Jan Mathias Köhler, Tobias Gindele, Leon Hetzel, Jakob Thaddäus Wiedemer, Sven Behnke:
Interpretable and Fine-Grained Visual Explanations for Convolutional Neural Networks. CoRR abs/1908.02686 (2019)
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