Thaddäus Wiedemer

According to our database, Thaddäus Wiedemer authored at least 9 papers between 2019 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Pretraining Frequency Predicts Compositional Generalization of CLIP on Real-World Tasks.

Thaddäus Wiedemer, Yash Sharma, Ameya Prabhu, Matthias Bethge, Wieland Brendel

CoRR, February, 2025

LLMs on the Line: Data Determines Loss-to-Loss Scaling Laws.

Prasanna Mayilvahanan, Thaddäus Wiedemer, Sayak Mallick, Matthias Bethge, Wieland Brendel

CoRR, February, 2025

In Search of Forgotten Domain Generalization.

Prasanna Mayilvahanan, Roland S. Zimmermann, Thaddäus Wiedemer, Evgenia Rusak, Attila Juhos, Matthias Bethge, Wieland Brendel

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Scale Learning in Scale-Equivariant Convolutional Networks.

Mark Basting, Robert-Jan Bruintjes, Thaddäus Wiedemer, Matthias Kümmerer, Matthias Bethge, Jan van Gemert

Proceedings of the 19th International Joint Conference on Computer Vision, 2024

Provable Compositional Generalization for Object-Centric Learning.

Thaddäus Wiedemer, Jack Brady, Alexander Panfilov, Attila Juhos, Matthias Bethge, Wieland Brendel

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Does CLIP's generalization performance mainly stem from high train-test similarity?

Prasanna Mayilvahanan, Thaddäus Wiedemer, Evgenia Rusak, Matthias Bethge, Wieland Brendel

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Compositional Generalization from First Principles.

Thaddäus Wiedemer, Prasanna Mayilvahanan, Matthias Bethge, Wieland Brendel

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Few-Shot Supervised Prototype Alignment for Pedestrian Detection on Fisheye Images.

Thaddäus Wiedemer, Stefan Wolf, Arne Schumann, Kaisheng Ma, Jürgen Beyerer

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

2019

Interpretable and Fine-Grained Visual Explanations for Convolutional Neural Networks.

Jörg Wagner, Jan Mathias Köhler, Tobias Gindele, Leon Hetzel, Jakob Thaddäus Wiedemer, Sven Behnke

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019