Evgenia Rusak

According to our database, Evgenia Rusak authored at least 13 papers between 2019 and 2026.

Collaborative distances:

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

2026

Low-Pass Filtering Improves Behavioral Alignment of Vision Models.

Max Wolff, Thomas Klein, Evgenia Rusak, Felix A. Wichmann, Wieland Brendel

CoRR, February, 2026

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 Proceedings on "I Can't Believe It's Not Better: Challenges in Applied Deep Learning" at ICLR 2025 Workshops, 2025

InfoNCE: Identifying the Gap Between Theory and Practice.

Evgenia Rusak, Patrik Reizinger, Attila Juhos, Oliver Bringmann, Roland S. Zimmermann, Wieland Brendel

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2025

2024

Focal Depth Estimation: A Calibration-Free, Subject- and Daytime Invariant Approach.

Benedikt W. Hosp, Björn Severitt, Rajat Agarwala, Evgenia Rusak, Yannick Sauer, Siegfried Wahl

CoRR, 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

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

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

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 Comput. Biol., March, 2023

2022

If your data distribution shifts, use self-learning.

Evgenia Rusak, Steffen Schneider, George Pachitariu, Luisa Eck, Peter Vincent Gehler, Oliver Bringmann, Wieland Brendel, Matthias Bethge

Trans. Mach. Learn. Res., 2022

2021

Adapting ImageNet-scale models to complex distribution shifts with self-learning.

Evgenia Rusak, Steffen Schneider, Peter V. Gehler, Oliver Bringmann, Wieland Brendel, Matthias Bethge

CoRR, 2021

2020

Increasing the robustness of DNNs against image corruptions by playing the Game of Noise.

Evgenia Rusak, Lukas Schott, Roland S. Zimmermann, Julian Bitterwolf, Oliver Bringmann, Matthias Bethge, Wieland Brendel

CoRR, 2020

Improving robustness against common corruptions by covariate shift adaptation.

Steffen Schneider, Evgenia Rusak, Luisa Eck, Oliver Bringmann, Wieland Brendel, Matthias Bethge

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

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

Proceedings of the Computer Vision - ECCV 2020, 2020

2019

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

CoRR, 2019