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2020 – today
- 2024
[c4]Amro Abbas, Evgenia Rusak, Kushal Tirumala, Wieland Brendel, Kamalika Chaudhuri, Ari S. Morcos:
Effective pruning of web-scale datasets based on complexity of concept clusters. ICLR 2024- [c3]Prasanna Mayilvahanan, Thaddäus Wiedemer, Evgenia Rusak, Matthias Bethge, Wieland Brendel:
Does CLIP's generalization performance mainly stem from high train-test similarity? ICLR 2024 - [i9]Amro Abbas, Evgenia Rusak, Kushal Tirumala, Wieland Brendel, Kamalika Chaudhuri, Ari S. Morcos:
Effective pruning of web-scale datasets based on complexity of concept clusters. CoRR abs/2401.04578 (2024) - [i8]Evgenia Rusak, Patrik Reizinger, Attila Juhos, Oliver Bringmann, Roland S. Zimmermann, Wieland Brendel:
InfoNCE: Identifying the Gap Between Theory and Practice. CoRR abs/2407.00143 (2024) - [i7]Benedikt W. Hosp, Björn Severitt, Rajat Agarwala, Evgenia Rusak, Yannick Sauer, Siegfried Wahl:
Focal Depth Estimation: A Calibration-Free, Subject- and Daytime Invariant Approach. CoRR abs/2408.03591 (2024) - [i6]Prasanna Mayilvahanan, Roland S. Zimmermann, Thaddäus Wiedemer, Evgenia Rusak, Attila Juhos, Matthias Bethge, Wieland Brendel:
In Search of Forgotten Domain Generalization. CoRR abs/2410.08258 (2024) - 2023
- [j2]Zhe Li
, Josue Ortega Caro, Evgenia Rusak, Wieland Brendel, Matthias Bethge, Fabio Anselmi, Ankit B. Patel, Andreas S. Tolias, Xaq Pitkow:
Robust deep learning object recognition models rely on low frequency information in natural images. PLoS Comput. Biol. 19(3) (2023) - [i5]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
- [j1]Evgenia Rusak, Steffen Schneider, George Pachitariu, Luisa Eck, Peter Vincent Gehler, Oliver Bringmann, Wieland Brendel, Matthias Bethge:
If your data distribution shifts, use self-learning. Trans. Mach. Learn. Res. 2022 (2022) - 2021
- [i4]Evgenia Rusak, Steffen Schneider, Peter V. Gehler, Oliver Bringmann, Wieland Brendel, Matthias Bethge:
Adapting ImageNet-scale models to complex distribution shifts with self-learning. CoRR abs/2104.12928 (2021) - 2020
- [c2]Evgenia Rusak, Lukas Schott, Roland S. Zimmermann, Julian Bitterwolf, Oliver Bringmann, Matthias Bethge, Wieland Brendel:
A Simple Way to Make Neural Networks Robust Against Diverse Image Corruptions. ECCV (3) 2020: 53-69 - [c1]Steffen Schneider, Evgenia Rusak, Luisa Eck, Oliver Bringmann, Wieland Brendel, Matthias Bethge:
Improving robustness against common corruptions by covariate shift adaptation. NeurIPS 2020 - [i3]Evgenia Rusak, Lukas Schott, Roland S. Zimmermann, Julian Bitterwolf, Oliver Bringmann, Matthias Bethge, Wieland Brendel:
Increasing the robustness of DNNs against image corruptions by playing the Game of Noise. CoRR abs/2001.06057 (2020) - [i2]Steffen Schneider, Evgenia Rusak, Luisa Eck, Oliver Bringmann, Wieland Brendel, Matthias Bethge:
Improving robustness against common corruptions by covariate shift adaptation. CoRR abs/2006.16971 (2020)
2010 – 2019
- 2019
- [i1]Claudio Michaelis, Benjamin Mitzkus, Robert Geirhos, Evgenia Rusak, Oliver Bringmann, Alexander S. Ecker, Matthias Bethge, Wieland Brendel:
Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming. CoRR abs/1907.07484 (2019)
Coauthor Index
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