Roland Simon Zimmermann
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A simple way to make neural networks robust against diverse image corruptions
E Rusak, L Schott, RS Zimmermann, J Bitterwolf, O Bringmann, M Bethge, ...
European Conference on Computer Vision (ECCV) 2020, 2020
Foolbox Native: Fast adversarial attacks to benchmark the robustness of machine learning models in PyTorch, TensorFlow, and JAX
J Rauber, R Zimmermann, M Bethge, W Brendel
Journal of Open Source Software 5 (53), 2607, 2020
Observing spatio-temporal dynamics of excitable media using reservoir computing
RS Zimmermann, U Parlitz
Chaos: An Interdisciplinary Journal of Nonlinear Science 28 (4), 043118, 2018
Contrastive Learning Inverts the Data Generating Process
RS Zimmermann, Y Sharma, S Schneider, M Bethge, W Brendel
International Conference of Machine Learning 2021 139, 12979-12990, 2021
Faster training of Mask R-CNN by focusing on instance boundaries
RS Zimmermann, JN Siems
Computer Vision and Image Understanding, 102795, 2019
Score-Based Generative Classifiers
RS Zimmermann, L Schott, Y Song, BA Dunn, DA Klindt
arXiv preprint arXiv:2110.00473, 2021
Exemplary Natural Images Explain CNN Activations Better than State-of-the-Art Feature Visualization
J Borowski, RS Zimmermann, J Schepers, R Geirhos, TSA Wallis, ...
International Conference on Learning Representations 2021, 2020
Comment on "Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network"
RS Zimmermann
arXiv preprint arXiv:1907.00895, 2019
How Well do Feature Visualizations Support Causal Understanding of CNN Activations?
RS Zimmermann, J Borowski, R Geirhos, M Bethge, T Wallis, W Brendel
Advances in Neural Information Processing Systems 34, 2021
Reconstructing Complex Cardiac Excitation Waves From Incomplete Data Using Echo State Networks and Convolutional Autoencoders
S Herzog, RS Zimmermann, J Abele, S Luther, U Parlitz
Frontiers in Applied Mathematics and Statistics 6, 616584, 2021
A self-supervised feature map augmentation (FMA) loss and combined augmentations finetuning to efficiently improve the robustness of CNNs
N Kapoor, C Yuan, J Löhdefink, R Zimmerman, S Varghese, F Hüger, ...
Proceedings of the 4th ACM Computer Science in Cars Symposium, 1-8, 2020
Increasing Confidence in Adversarial Robustness Evaluations
RS Zimmermann, W Brendel, F Tramer, N Carlini
NeurIPS 2022, 2022
Simion Zoo: A Workbench for Distributed Experimentation with Reinforcement Learning for Continuous Control Tasks
B Fernandez-Gauna, M Graña, RS Zimmermann
arXiv preprint arXiv:1904.07817, 2019
Provably Learning Object-Centric Representations
J Brady, RS Zimmermann, Y Sharma, B Schölkopf, J von Kügelgen, ...
arXiv preprint arXiv:2305.14229, 2023
Content suppresses style: dimensionality collapse in contrastive learning
E Rusak, P Reizinger, RS Zimmermann, O Bringmann, W Brendel
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