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R. Zimmermann · SciRah

Researcher profile · Semantic Scholar

R. Zimmermann

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R. Zimmermann — researcher profile on SciRah

h-index: 17
Works: 27
Citations: 1,640

Most-cited papers

Contrastive Learning Inverts the Data Generating Process
R. Zimmermann, Yash Sharma, S. Schneider, M. Bethge +1 more
2021International Conference on Machine Learning297 citations
Semantic Scholar
A Simple Way to Make Neural Networks Robust Against Diverse Image Corruptions
E. Rusak, Lukas Schott, R. Zimmermann, Julian Bitterwolf +3 more
2020European Conference on Computer Vision252 citations Open access
Semantic Scholar
Foolbox Native: Fast adversarial attacks to benchmark the robustness of machine learning models in PyTorch, TensorFlow, and JAX
Jonas Rauber, R. Zimmermann, M. Bethge, Wieland Brendel
2020Journal of Open Source Software208 citations Open access
Semantic Scholar
Observing spatio-temporal dynamics of excitable media using reservoir computing.
R. Zimmermann, U. Parlitz
2018Chaos173 citations
Semantic Scholar
InfoNCE: Identifying the Gap Between Theory and Practice
E. Rusak, P. Reizinger, A. Juhos, Oliver Bringmann +2 more
2024International Conference on Artificial Intelligence and Statistics81 citations
Semantic Scholar
Score-Based Generative Classifiers
R. Zimmermann, Lukas Schott, Yang Song, Benjamin A. Dunn +1 more
2021arXiv.org79 citations
Semantic Scholar
Faster Training of Mask R-CNN by Focusing on Instance Boundaries
R. Zimmermann, Julien Siems
2018Computer Vision and Image Understanding73 citations Open access
Semantic Scholar
Increasing the robustness of DNNs against image corruptions by playing the Game of Noise
E. Rusak, Lukas Schott, R. Zimmermann, Julian Bitterwolf +3 more
2020arXiv.org67 citations
Semantic Scholar
Smart Grid for Industry Using Multi-Agent Reinforcement Learning
M. Roesch, C. Linder, R. Zimmermann, Andreas Rudolf +2 more
2020Applied Sciences61 citations Open access
Semantic Scholar
Provably Learning Object-Centric Representations
Jack Brady, R. Zimmermann, Yash Sharma, B. Schölkopf +2 more
2023International Conference on Machine Learning58 citations Open access
Semantic Scholar
Exemplary Natural Images Explain CNN Activations Better than State-of-the-Art Feature Visualization
Judy Borowski, R. Zimmermann, Judith Schepers, Robert Geirhos +3 more
2021International Conference on Learning Representations49 citations
Semantic Scholar
How Well do Feature Visualizations Support Causal Understanding of CNN Activations?
R. Zimmermann, Judy Borowski, Robert Geirhos, M. Bethge +2 more
2021Neural Information Processing Systems47 citations
Semantic Scholar
Don't trust your eyes: on the (un)reliability of feature visualizations
Robert Geirhos, R. Zimmermann, Blair Bilodeau, Wieland Brendel +1 more
2023International Conference on Machine Learning44 citations Open access
Semantic Scholar
Scale Alone Does not Improve Mechanistic Interpretability in Vision Models
R. Zimmermann, Thomas Klein, Wieland Brendel
2023Neural Information Processing Systems33 citations Open access
Semantic Scholar
Comment on "Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network"
R. Zimmermann
2019arXiv.org28 citations
Semantic Scholar
In Search of Forgotten Domain Generalization
Prasanna Mayilvahanan, R. Zimmermann, Thaddäus Wiedemer, E. Rusak +3 more
2024arXiv.org27 citations
Semantic Scholar
Increasing Confidence in Adversarial Robustness Evaluations
R. Zimmermann, Wieland Brendel, Florian Tramèr, Nicholas Carlini
2022Neural Information Processing Systems25 citations Open access
Semantic Scholar
Sensitivity of Slot-Based Object-Centric Models to their Number of Slots
R. Zimmermann, Sjoerd van Steenkiste, Mehdi S. M. Sajjadi, Thomas Kipf +1 more
2023arXiv.org8 citations Open access
Semantic Scholar
Reconstructing Complex Cardiac Excitation Waves From Incomplete Data Using Echo State Networks and Convolutional Autoencoders
S. Herzog, R. Zimmermann, J. Abele, S. Luther +1 more
2021Frontiers in Applied Mathematics and Statistics8 citations Open access
Semantic Scholar
Exemplary Natural Images Explain CNN Activations Better than Feature Visualizations
Judy Borowski, R. Zimmermann, Judith Schepers, Robert Geirhos +3 more
2020arXiv.org7 citations
Semantic Scholar
LAION-C: An Out-of-Distribution Benchmark for Web-Scale Vision Models
Fanfei Li, Thomas Klein, W. Brendel, Robert Geirhos +1 more
2025International Conference on Machine Learning6 citations
Semantic Scholar
Measuring Per-Unit Interpretability at Scale Without Humans
R. Zimmermann, David A. Klindt, Wieland Brendel
2024Neural Information Processing Systems5 citations
Semantic Scholar
Content suppresses style: dimensionality collapse in contrastive learning
E. Rusak, P. Reizinger, R. Zimmermann, O. Bringmann +1 more
20225 citations
Semantic Scholar
Natural images are more informative for interpreting CNN activations than synthetic feature visualizations
Judy Borowski, R. Zimmermann, Judith Schepers, Robert Geirhos +3 more
20204 citations
Semantic Scholar
In Search of Forgotten Domain Generalization
Prasanna Mayilvahanan, R. Zimmermann, Thaddäus Wiedemer, E. Rusak +3 more
2025International Conference on Learning Representations0 citations
Semantic Scholar
Understanding Machine Perception: How Do Neural Networks Represent the World?
R. Zimmermann
20250 citations
Semantic Scholar
Simion Zoo: A Workbench for Distributed Experimentation with Reinforcement Learning for Continuous Control Tasks
B. Fernández-Gauna, M. Graña, R. Zimmermann
2019arXiv.org0 citations
Semantic Scholar

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