Evgenia Rusak
Evgenia Rusak
University of Tübingen
Dpt. of Computer Science
Embedded Systems
Sand 13
72076 Tübingen
Germany
- Telephone
- +49 - (0) 70 71 - 29 - 78997
- Telefax
- +49 - (0) 70 71 - 29 - 50 62
- Office
- Sand 13, B201
- Office hours
- by appointment
Website: https://evgeniarusak.github.io/
Research Interests
During my PhD, I have been working on improving the generalization capabilities of Deep Neural Networks beyond their training distribution. I have explored how we can make vision models more robust to distribution shifts. Beyond investigating different robustification methods, I have also analyzed the benefits of continual learning when the model is allowed to adapt to the encountered distribution shifts.
Publications
2021
Adapting ImageNet-Scale Models to Complex Distribution Shifts with Self-Learning
by Evgenia Rusak, Steffen Schneider, Peter Gehler, Oliver Bringmann, Wieland Brendel, and Matthias BethgeIn arXiv preprint arXiv:2104.12928, 2021.
2020
Improving Robustness against Common Corruptions by Covariate Shift Adaptation
by Steffen Schneider, Evgenia Rusak, Luisa Eck, Oliver Bringmann, Wieland Brendel, and Matthias BethgeIn Advances in Neural Information Processing Systems 33, 2020.
A Simple Way to Make Neural Networks Robust against Diverse Image Corruptions
by Evgenia Rusak, Lukas Schott, Roland S Zimmermann, Julian Bitterwolf, Oliver Bringmann, Matthias Bethge, and Wieland BrendelIn European Conference on Computer Vision, pages 53–69. Springer, Cham, 2020.
Increasing the Robustness of DNNs against Image Corruptions by Playing the Game of Noise
by Evgenia Rusak, Lukas Schott, Roland S Zimmermann, Julian Bitterwolf, Oliver Bringmann, Matthias Bethge, and Wieland BrendelPeer-reviewed publication, 2020.
2019
Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming
by Claudio Michaelis, Benjamin Mitzkus, Robert Geirhos, Evgenia Rusak, Oliver Bringmann, Alexander S. Ecker, Matthias Bethge, and Wieland BrendelIn CoRR abs/1907.07484, 2019.
2018
An Artificial Neural Network for Automated Fault Detection
by Evgenia Rusak, Julian Bitterwolf, Sebastian Reiter, Alexander Viehl, and Oliver BringmannPeer-reviewed publication, pages 141–147, 2018.
Research projects
Teaching
| Advanced Topics in Embedded Systems | Summer 2019 |
|---|---|
| Efficient Machine Learning in Hardware | Summer 2021 Summer 2022 |
| Moderne Architekturen Eingebetteter Systeme | Winter 2019 Winter 2020 |
| Proseminar: Moderne Architekturen Eingebetteter Systeme | Winter 2021 |