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ORCIDRoland S. Zimmermann
Person information
- affiliation: University of Tübingen, Germany
- affiliation (former): Volkswagen AG Wolfsburg, Germany
- affiliation (former): University of Göttingen, Germany
Other persons with the same name
- Roland Zimmermann 0001
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— Georg Simon Ohm University of Applied Sciences Nuremberg, Germany (and 1 more)
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2020 – today
- 2026
[i22]Max Kaufmann, David Lindner, Roland S. Zimmermann, Rohin Shah:
Aligned, Orthogonal or In-conflict: When can we safely optimize Chain-of-Thought? CoRR abs/2603.30036 (2026)- 2025
- [c14]Evgenia Rusak, Patrik Reizinger, Attila Juhos, Oliver Bringmann, Roland S. Zimmermann, Wieland Brendel:
InfoNCE: Identifying the Gap Between Theory and Practice. AISTATS 2025: 4159-4167 - [c13]Prasanna Mayilvahanan, Roland S. Zimmermann, Thaddäus Wiedemer, Evgenia Rusak, Attila Juhos, Matthias Bethge, Wieland Brendel:
In Search of Forgotten Domain Generalization. ICLR 2025: 90-130 - [c12]Prasanna Mayilvahanan, Roland S. Zimmermann, Thaddäus Wiedemer, Evgenia Rusak, Attila Juhos, Matthias Bethge, Wieland Brendel:
In Search of Forgotten Domain Generalization. ICLR 2025 - [c11]Fanfei Li, Thomas Klein, Wieland Brendel, Robert Geirhos, Roland S. Zimmermann:
LAION-C: An Out-of-Distribution Benchmark for Web-Scale Vision Models. ICML 2025 - [i21]Mary Phuong, Roland S. Zimmermann, Ziyue Wang, David Lindner, Victoria Krakovna, Sarah Cogan, Allan Dafoe, Lewis Ho, Rohin Shah:
Evaluating Frontier Models for Stealth and Situational Awareness. CoRR abs/2505.01420 (2025) - [i20]Fanfei Li, Thomas Klein, Wieland Brendel, Robert Geirhos, Roland S. Zimmermann:
LAION-C: An Out-of-Distribution Benchmark for Web-Scale Vision Models. CoRR abs/2506.16950 (2025) - [i19]Artur Zolkowski, Kei Nishimura-Gasparian, Robert McCarthy, Roland S. Zimmermann, David Lindner:
Early Signs of Steganographic Capabilities in Frontier LLMs. CoRR abs/2507.02737 (2025) - [i18]Scott Emmons, Roland S. Zimmermann, David K. Elson, Rohin Shah:
A Pragmatic Way to Measure Chain-of-Thought Monitorability. CoRR abs/2510.23966 (2025) - [i17]David Lindner, Charlie Griffin, Tomek Korbak, Roland S. Zimmermann, Geoffrey Irving, Sebastian Farquhar, Alan Cooney:
Practical challenges of control monitoring in frontier AI deployments. CoRR abs/2512.22154 (2025) - 2024
- [c10]Robert Geirhos, Roland S. Zimmermann, Blair L. Bilodeau, Wieland Brendel, Been Kim:
Don't trust your eyes: on the (un)reliability of feature visualizations. ICML 2024: 15294-15330 - [c9]Roland S. Zimmermann, David A. Klindt, Wieland Brendel:
Measuring Per-Unit Interpretability at Scale Without Humans. NeurIPS 2024 - [i16]Evgenia Rusak, Patrik Reizinger, Attila Juhos, Oliver Bringmann, Roland S. Zimmermann, Wieland Brendel:
InfoNCE: Identifying the Gap Between Theory and Practice. CoRR abs/2407.00143 (2024) - [i15]Prasanna Mayilvahanan, Roland S. Zimmermann, Thaddäus Wiedemer, Evgenia Rusak, Attila Juhos, Matthias Bethge, Wieland Brendel:
In Search of Forgotten Domain Generalization. CoRR abs/2410.08258 (2024) - 2023
- [c8]Jack Brady, Roland S. Zimmermann, Yash Sharma, Bernhard Schölkopf, Julius von Kügelgen, Wieland Brendel:
Provably Learning Object-Centric Representations. ICML 2023: 3038-3062 - [c7]Roland S. Zimmermann, Thomas Klein, Wieland Brendel:
Scale Alone Does not Improve Mechanistic Interpretability in Vision Models. NeurIPS 2023 - [i14]Jack Brady, Roland S. Zimmermann, Yash Sharma, Bernhard Schölkopf, Julius von Kügelgen, Wieland Brendel:
Provably Learning Object-Centric Representations. CoRR abs/2305.14229 (2023) - [i13]Roland S. Zimmermann, Sjoerd van Steenkiste, Mehdi S. M. Sajjadi, Thomas Kipf, Klaus Greff:
Sensitivity of Slot-Based Object-Centric Models to their Number of Slots. CoRR abs/2305.18890 (2023) - [i12]Robert Geirhos, Roland S. Zimmermann, Blair L. Bilodeau, Wieland Brendel, Been Kim:
Don't trust your eyes: on the (un)reliability of feature visualizations. CoRR abs/2306.04719 (2023) - [i11]Roland S. Zimmermann, Thomas Klein, Wieland Brendel:
Scale Alone Does not Improve Mechanistic Interpretability in Vision Models. CoRR abs/2307.05471 (2023) - 2022
- [c6]Roland S. Zimmermann, Wieland Brendel, Florian Tramèr, Nicholas Carlini:
Increasing Confidence in Adversarial Robustness Evaluations. NeurIPS 2022 - [i10]Roland S. Zimmermann, Wieland Brendel, Florian Tramèr, Nicholas Carlini:
Increasing Confidence in Adversarial Robustness Evaluations. CoRR abs/2206.13991 (2022) - 2021
- [c5]Judy Borowski, Roland Simon Zimmermann, Judith Schepers, Robert Geirhos, Thomas S. A. Wallis, Matthias Bethge, Wieland Brendel:
Exemplary Natural Images Explain CNN Activations Better than State-of-the-Art Feature Visualization. ICLR 2021 - [c4]Roland S. Zimmermann, Yash Sharma, Steffen Schneider, Matthias Bethge, Wieland Brendel:
Contrastive Learning Inverts the Data Generating Process. ICML 2021: 12979-12990 - [c3]Roland S. Zimmermann, Judy Borowski, Robert Geirhos, Matthias Bethge, Thomas S. A. Wallis, Wieland Brendel:
How Well do Feature Visualizations Support Causal Understanding of CNN Activations? NeurIPS 2021: 11730-11744 - [i9]Roland S. Zimmermann, Yash Sharma, Steffen Schneider, Matthias Bethge, Wieland Brendel:
Contrastive Learning Inverts the Data Generating Process. CoRR abs/2102.08850 (2021) - [i8]Roland S. Zimmermann, Judy Borowski, Robert Geirhos, Matthias Bethge, Thomas S. A. Wallis, Wieland Brendel:
How Well do Feature Visualizations Support Causal Understanding of CNN Activations? CoRR abs/2106.12447 (2021) - [i7]Roland S. Zimmermann, Lukas Schott, Yang Song, Benjamin A. Dunn, David A. Klindt:
Score-Based Generative Classifiers. CoRR abs/2110.00473 (2021) - 2020
- [j3]Sebastian Herzog, Roland S. Zimmermann, Johannes Abele, Stefan Luther, Ulrich Parlitz:
Reconstructing Complex Cardiac Excitation Waves From Incomplete Data Using Echo State Networks and Convolutional Autoencoders. Frontiers Appl. Math. Stat. 6: 616584 (2020) - [j2]Jonas Rauber, Roland Zimmermann, Matthias Bethge, Wieland Brendel:
Foolbox Native: Fast adversarial attacks to benchmark the robustness of machine learning models in PyTorch, TensorFlow, and JAX. J. Open Source Softw. 5(53): 2607 (2020) - [c2]Nikhil Kapoor, Chun Yuan, Jonas Löhdefink, Roland Zimmermann, Serin Varghese, Fabian Hüger, Nico M. Schmidt, Peter Schlicht, Tim Fingscheidt:
A Self-Supervised Feature Map Augmentation (FMA) Loss and Combined Augmentations Finetuning to Efficiently Improve the Robustness of CNNs. CSCS 2020: 3:1-3:8 - [c1]Evgenia Rusak, Lukas Schott, Roland S. Zimmermann, Julian Bitterwolf, Oliver Bringmann, Matthias Bethge, Wieland Brendel:
A Simple Way to Make Neural Networks Robust Against Diverse Image Corruptions. ECCV (3) 2020: 53-69 - [i6]Evgenia Rusak, Lukas Schott, Roland S. Zimmermann, Julian Bitterwolf, Oliver Bringmann, Matthias Bethge, Wieland Brendel:
Increasing the robustness of DNNs against image corruptions by playing the Game of Noise. CoRR abs/2001.06057 (2020) - [i5]Judy Borowski, Roland S. Zimmermann, Judith Schepers, Robert Geirhos, Thomas S. A. Wallis, Matthias Bethge, Wieland Brendel:
Exemplary Natural Images Explain CNN Activations Better than Feature Visualizations. CoRR abs/2010.12606 (2020) - [i4]Nikhil Kapoor, Chun Yuan, Jonas Löhdefink, Roland Zimmermann, Serin Varghese, Fabian Hüger, Nico M. Schmidt, Peter Schlicht, Tim Fingscheidt:
A Self-Supervised Feature Map Augmentation (FMA) Loss and Combined Augmentations Finetuning to Efficiently Improve the Robustness of CNNs. CoRR abs/2012.01386 (2020)
2010 – 2019
- 2019
- [j1]Roland S. Zimmermann, Julien N. Siems:
Faster training of Mask R-CNN by focusing on instance boundaries. Comput. Vis. Image Underst. 188 (2019) - [i3]Borja Fernández-Gauna, Manuel Graña, Roland S. Zimmermann:
Simion Zoo: A Workbench for Distributed Experimentation with Reinforcement Learning for Continuous Control Tasks. CoRR abs/1904.07817 (2019) - [i2]Roland S. Zimmermann:
Comment on "Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network". CoRR abs/1907.00895 (2019) - 2018
- [i1]Roland S. Zimmermann, Julien N. Siems:
Faster Training of Mask R-CNN by Focusing on Instance Boundaries. CoRR abs/1809.07069 (2018)
Coauthor Index
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