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ORCIDRobert Geirhos
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2020 – today
- 2024
[c14]Priyank Jaini, Kevin Clark, Robert Geirhos:
Intriguing Properties of Generative Classifiers. ICLR 2024- [c13]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 - [i23]Paul Gavrikov, Jovita Lukasik, Steffen Jung, Robert Geirhos, Bianca Lamm, Muhammad Jehanzeb Mirza, Margret Keuper, Janis Keuper:
Are Vision Language Models Texture or Shape Biased and Can We Steer Them? CoRR abs/2403.09193 (2024) - [i22]Jannis Ahlert, Thomas Klein, Felix A. Wichmann, Robert Geirhos:
How Aligned are Different Alignment Metrics? CoRR abs/2407.07530 (2024) - [i21]Robert Geirhos, Priyank Jaini, Austin Stone, Sourabh Medapati, Xi Yi, George Toderici, Abhijit Ogale, Jonathon Shlens:
Towards flexible perception with visual memory. CoRR abs/2408.08172 (2024) - 2023
- [c12]Mostafa Dehghani, Josip Djolonga, Basil Mustafa, Piotr Padlewski, Jonathan Heek, Justin Gilmer, Andreas Peter Steiner, Mathilde Caron, Robert Geirhos, Ibrahim Alabdulmohsin, Rodolphe Jenatton, Lucas Beyer, Michael Tschannen, Anurag Arnab, Xiao Wang, Carlos Riquelme Ruiz, Matthias Minderer, Joan Puigcerver, Utku Evci, Manoj Kumar, Sjoerd van Steenkiste, Gamaleldin Fathy Elsayed, Aravindh Mahendran, Fisher Yu, Avital Oliver, Fantine Huot, Jasmijn Bastings, Mark Collier, Alexey A. Gritsenko, Vighnesh Birodkar, Cristina Nader Vasconcelos, Yi Tay, Thomas Mensink, Alexander Kolesnikov, Filip Pavetic, Dustin Tran, Thomas Kipf, Mario Lucic, Xiaohua Zhai, Daniel Keysers, Jeremiah J. Harmsen, Neil Houlsby:
Scaling Vision Transformers to 22 Billion Parameters. ICML 2023: 7480-7512 - [c11]Mostafa Dehghani, Basil Mustafa, Josip Djolonga, Jonathan Heek, Matthias Minderer, Mathilde Caron, Andreas Steiner, Joan Puigcerver, Robert Geirhos, Ibrahim M. Alabdulmohsin, Avital Oliver, Piotr Padlewski, Alexey A. Gritsenko, Mario Lucic, Neil Houlsby:
Patch n' Pack: NaViT, a Vision Transformer for any Aspect Ratio and Resolution. NeurIPS 2023 - [i20]Mostafa Dehghani, Josip Djolonga, Basil Mustafa, Piotr Padlewski, Jonathan Heek, Justin Gilmer, Andreas Steiner, Mathilde Caron, Robert Geirhos, Ibrahim Alabdulmohsin, Rodolphe Jenatton, Lucas Beyer, Michael Tschannen, Anurag Arnab, Xiao Wang
, Carlos Riquelme, Matthias Minderer, Joan Puigcerver, Utku Evci, Manoj Kumar, Sjoerd van Steenkiste, Gamaleldin F. Elsayed, Aravindh Mahendran, Fisher Yu, Avital Oliver, Fantine Huot, Jasmijn Bastings, Mark Patrick Collier, Alexey A. Gritsenko, Vighnesh Birodkar, Cristina Nader Vasconcelos, Yi Tay, Thomas Mensink, Alexander Kolesnikov, Filip Pavetic, Dustin Tran, Thomas Kipf, Mario Lucic, Xiaohua Zhai, Daniel Keysers, Jeremiah Harmsen, Neil Houlsby:
Scaling Vision Transformers to 22 Billion Parameters. CoRR abs/2302.05442 (2023) - [i19]Felix A. Wichmann, Robert Geirhos:
Are Deep Neural Networks Adequate Behavioural Models of Human Visual Perception? CoRR abs/2305.17023 (2023) - [i18]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) - [i17]Mostafa Dehghani, Basil Mustafa, Josip Djolonga, Jonathan Heek, Matthias Minderer, Mathilde Caron, Andreas Steiner, Joan Puigcerver, Robert Geirhos, Ibrahim Alabdulmohsin, Avital Oliver, Piotr Padlewski, Alexey A. Gritsenko, Mario Lucic, Neil Houlsby:
Patch n' Pack: NaViT, a Vision Transformer for any Aspect Ratio and Resolution. CoRR abs/2307.06304 (2023) - [i16]Priyank Jaini, Kevin Clark, Robert Geirhos:
Intriguing properties of generative classifiers. CoRR abs/2309.16779 (2023) - [i15]Ilia Sucholutsky, Lukas Muttenthaler, Adrian Weller, Andi Peng, Andreea Bobu, Been Kim, Bradley C. Love, Erin Grant, Jascha Achterberg, Joshua B. Tenenbaum, Katherine M. Collins, Katherine L. Hermann, Kerem Oktar, Klaus Greff, Martin N. Hebart, Nori Jacoby, Qiuyi Zhang, Raja Marjieh, Robert Geirhos, Sherol Chen, Simon Kornblith, Sunayana Rane, Talia Konkle, Thomas P. O'Connell, Thomas Unterthiner, Andrew K. Lampinen, Klaus-Robert Müller, Mariya Toneva, Thomas L. Griffiths:
Getting aligned on representational alignment. CoRR abs/2310.13018 (2023) - [i14]Felix A. Wichmann, Simon Kornblith, Robert Geirhos:
Neither hype nor gloom do DNNs justice. CoRR abs/2312.05355 (2023) - 2022
- [b1]Robert Geirhos:
To err is human? A functional comparison of human and machine decision-making. University of Tübingen, Germany, 2022 - [c10]Kristof Meding, Luca M. Schulze Buschoff, Robert Geirhos, Felix A. Wichmann:
Trivial or Impossible --- dichotomous data difficulty masks model differences (on ImageNet and beyond). ICLR 2022 - [c9]Ben Sorscher, Robert Geirhos, Shashank Shekhar, Surya Ganguli, Ari Morcos:
Beyond neural scaling laws: beating power law scaling via data pruning. NeurIPS 2022 - [p1]Robert Geirhos:
Irren ist menschlich: Aber was, wenn Maschinen Fehler machen? Ausgezeichnete Informatikdissertationen 2022: 51-60 - [i13]Lukas S. Huber, Robert Geirhos, Felix A. Wichmann:
The developmental trajectory of object recognition robustness: children are like small adults but unlike big deep neural networks. CoRR abs/2205.10144 (2022) - [i12]Ben Sorscher, Robert Geirhos, Shashank Shekhar, Surya Ganguli, Ari S. Morcos:
Beyond neural scaling laws: beating power law scaling via data pruning. CoRR abs/2206.14486 (2022) - 2021
- [c8]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 - [c7]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 - [c6]Robert Geirhos, Kantharaju Narayanappa, Benjamin Mitzkus, Tizian Thieringer, Matthias Bethge, Felix A. Wichmann, Wieland Brendel:
Partial success in closing the gap between human and machine vision. NeurIPS 2021: 23885-23899 - [i11]Robert Geirhos, Kantharaju Narayanappa, Benjamin Mitzkus, Tizian Thieringer, Matthias Bethge, Felix A. Wichmann, Wieland Brendel:
Partial success in closing the gap between human and machine vision. CoRR abs/2106.07411 (2021) - [i10]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) - [i9]Kristof Meding, Luca M. Schulze Buschoff, Robert Geirhos, Felix A. Wichmann:
Trivial or impossible - dichotomous data difficulty masks model differences (on ImageNet and beyond). CoRR abs/2110.05922 (2021) - 2020
- [j1]Robert Geirhos, Jörn-Henrik Jacobsen, Claudio Michaelis, Richard S. Zemel, Wieland Brendel, Matthias Bethge, Felix A. Wichmann:
Shortcut learning in deep neural networks. Nat. Mach. Intell. 2(11): 665-673 (2020) - [c5]Robert Geirhos, Kristof Meding, Felix A. Wichmann:
Beyond accuracy: quantifying trial-by-trial behaviour of CNNs and humans by measuring error consistency. NeurIPS 2020 - [i8]Robert Geirhos, Jörn-Henrik Jacobsen, Claudio Michaelis, Richard S. Zemel, Wieland Brendel, Matthias Bethge, Felix A. Wichmann:
Shortcut Learning in Deep Neural Networks. CoRR abs/2004.07780 (2020) - [i7]Robert Geirhos, Kristof Meding, Felix A. Wichmann:
Beyond accuracy: quantifying trial-by-trial behaviour of CNNs and humans by measuring error consistency. CoRR abs/2006.16736 (2020) - [i6]Robert Geirhos, Kantharaju Narayanappa, Benjamin Mitzkus, Matthias Bethge, Felix A. Wichmann, Wieland Brendel:
On the surprising similarities between supervised and self-supervised models. CoRR abs/2010.08377 (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)
2010 – 2019
- 2019
- [c4]Robert Geirhos, Patricia Rubisch, Claudio Michaelis, Matthias Bethge, Felix A. Wichmann, Wieland Brendel:
ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness. ICLR 2019 - [i4]Claudio Michaelis, Benjamin Mitzkus, Robert Geirhos, Evgenia Rusak, Oliver Bringmann, Alexander S. Ecker, Matthias Bethge, Wieland Brendel:
Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming. CoRR abs/1907.07484 (2019) - 2018
- [c3]Robert Geirhos, Carlos R. Medina Temme, Jonas Rauber, Heiko H. Schütt, Matthias Bethge, Felix A. Wichmann:
Generalisation in humans and deep neural networks. NeurIPS 2018: 7549-7561 - [i3]Robert Geirhos, Carlos R. Medina Temme, Jonas Rauber, Heiko H. Schütt, Matthias Bethge, Felix A. Wichmann:
Generalisation in humans and deep neural networks. CoRR abs/1808.08750 (2018) - [i2]Robert Geirhos, Patricia Rubisch, Claudio Michaelis, Matthias Bethge, Felix A. Wichmann, Wieland Brendel:
ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness. CoRR abs/1811.12231 (2018) - 2017
- [c2]Felix A. Wichmann, David H. J. Janssen, Robert Geirhos, Guillermo Aguilar, Heiko H. Schütt, Marianne Maertens, Matthias Bethge:
Methods and measurements to compare men against machines. HVEI 2017: 36-45 - [i1]Robert Geirhos, David H. J. Janssen, Heiko H. Schütt, Jonas Rauber, Matthias Bethge, Felix A. Wichmann:
Comparing deep neural networks against humans: object recognition when the signal gets weaker. CoRR abs/1706.06969 (2017) - 2015
- [c1]Martin V. Butz, Robert Geirhos, Jan Kneissler:
An Automatized Heider-Simmel Story Generation Tool. CogSci 2015
Coauthor Index
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