Roland S. Zimmermann

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 22

Top Topics

Knowledge Domains

Top Venues

Comput. Vis. Image Underst.

Publications

Evgenia Rusak, Patrik Reizinger, Attila Juhos, Oliver Bringmann, Roland S. Zimmermann, Wieland Brendel
InfoNCE: Identifying the Gap Between Theory and Practice. CoRR (2024)
Jack Brady, Roland S. Zimmermann, Yash Sharma, Bernhard Schölkopf, Julius von Kügelgen, Wieland Brendel
Provably Learning Object-Centric Representations. CoRR (2023)
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 (2023)
Jack Brady, Roland S. Zimmermann, Yash Sharma, Bernhard Schölkopf, Julius von Kügelgen, Wieland Brendel
Provably Learning Object-Centric Representations. ICML (2023)
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 (2023)
Roland S. Zimmermann, Thomas Klein, Wieland Brendel
Scale Alone Does not Improve Mechanistic Interpretability in Vision Models. NeurIPS (2023)
Roland S. Zimmermann, Thomas Klein, Wieland Brendel
Scale Alone Does not Improve Mechanistic Interpretability in Vision Models. CoRR (2023)
Roland S. Zimmermann, Wieland Brendel, Florian Tramèr, Nicholas Carlini
Increasing Confidence in Adversarial Robustness Evaluations. CoRR (2022)
Roland S. Zimmermann, Wieland Brendel, Florian Tramèr, Nicholas Carlini
Increasing Confidence in Adversarial Robustness Evaluations. NeurIPS (2022)
Roland S. Zimmermann, Yash Sharma, Steffen Schneider, Matthias Bethge, Wieland Brendel
Contrastive Learning Inverts the Data Generating Process. ICML (2021)
Roland S. Zimmermann, Yash Sharma, Steffen Schneider, Matthias Bethge, Wieland Brendel
Contrastive Learning Inverts the Data Generating Process. CoRR (2021)
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 (2021)
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)
Roland S. Zimmermann, Lukas Schott, Yang Song, Benjamin A. Dunn, David A. Klindt
Score-Based Generative Classifiers. CoRR (2021)
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 (2020)
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 (2020)
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)
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 (2020)
Roland S. Zimmermann
Comment on "Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network". CoRR (2019)
Borja Fernández-Gauna, Manuel Graña, Roland S. Zimmermann
Simion Zoo: A Workbench for Distributed Experimentation with Reinforcement Learning for Continuous Control Tasks. CoRR (2019)
Roland S. Zimmermann, Julien N. Siems
Faster training of Mask R-CNN by focusing on instance boundaries. Comput. Vis. Image Underst. 188 (2019)
Roland S. Zimmermann, Julien N. Siems
Faster Training of Mask R-CNN by Focusing on Instance Boundaries. CoRR (2018)