Publications (Machine Learning)

You can also find my articles on my Google Scholar profile.

Effective pruning of web-scale datasets based on complexity of concept clusters
Amro Abbas*, Evgenia Rusak*, Kushal Tirumala, Wieland Brendel, Kamalika Chaudhuri, Ari S. Morcos, ICLR 2024
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Does CLIP’s generalization performance mainly stem from high train-test similarity?
Prasanna Mayilvahanan*, Thaddäus Wiedemer*, Evgenia Rusak, Matthias Bethge, Wieland Brendel, ICLR 2024
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Removing High Frequency Information Improves DNN Behavioral Alignment
Max Wolff, Evgenia Rusak, Wieland Brendel, Workshop on Representational Alignment, ICLR 2024

Robust deep learning object recognition models rely on low frequency information in natural images
Zhe Li, Josue Ortega Caro, Evgenia Rusak, Wieland Brendel, Matthias Bethge, Fabio Anselmi, Ankit B. Patel Andreas S. Tolias, Xaq Pitkow , PLOS Computational Biology 2023
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ImageNet-D: A new challenging robustness dataset inspired by domain adaptation
Evgenia Rusak, Steffen Schneider, Peter Vincent Gehler, Oliver Bringmann, Wieland Brendel, Matthias Bethge, ShiftHappens Workshop at ICML 2022
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If your data distribution shifts, use self-learning
Evgenia Rusak, Steffen Schneider, George Pachitariu, Luisa Eck, Peter Gehler, Oliver Bringmann, Wieland Brendel, Matthias Bethge, TMLR 2022
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Improving robustness against common corruptions by covariate shift adaptation
Steffen Schneider*, Evgenia Rusak*, Luisa Eck, Oliver Bringmann, Wieland Brendel, Matthias Bethge, NeurIPS 2020
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A simple way to make neural networks robust against diverse image corruptions
Evgenia Rusak*, Lukas Schott*, Roland S. Zimmermann*, Julian Bitterwolf, Oliver Bringmann, Matthias Bethge, Wieland Brendel, oral at ECCV 2020
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Benchmarking robustness in object detection: Autonomous driving when winter is coming
Claudio Michaelis*, Benjamin Mitzkus*, Robert Geirhos*, Evgenia Rusak*, Oliver Bringmann, Alexander S. Ecker, Matthias Bethge, Wieland Brendel, The Machine Learning for Autonomous Driving Workshop, NeurIPS 2019
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