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Robert Geirhos
Robert Geirhos
Research Scientist, Google Brain
Verified email at google.com - Homepage
Title
Cited by
Cited by
Year
ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness
R Geirhos, P Rubisch, C Michaelis, M Bethge, FA Wichmann, W Brendel
Oral @ International Conference on Learning Representations (ICLR 2019), 2019
15722019
Shortcut Learning in Deep Neural Networks
R Geirhos, JH Jacobsen, C Michaelis, R Zemel, W Brendel, M Bethge, ...
Nature Machine Intelligence 2 (11), 665-673, 2020
6342020
Generalisation in humans and deep neural networks
R Geirhos, CR Medina Temme, J Rauber, HH Schütt, M Bethge, ...
Advances in Neural Information Processing Systems 31 (NeurIPS 2018), 2018
3842018
Comparing deep neural networks against humans: object recognition when the signal gets weaker
R Geirhos, DHJ Janssen, HH Schütt, J Rauber, M Bethge, FA Wichmann
arXiv preprint arXiv:1706.06969, 2017
2352017
Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming
C Michaelis, B Mitzkus, R Geirhos, E Rusak, O Bringmann, AS Ecker, ...
Machine Learning for Autonomous Driving Workshop (NeurIPS 2019), 2019
1842019
Beyond accuracy: quantifying trial-by-trial behaviour of CNNs and humans by measuring error consistency
R Geirhos, K Meding, FA Wichmann
Advances in Neural Information Processing Systems 33 (NeurIPS 2020), 2020
432020
On the surprising similarities between supervised and self-supervised models
R Geirhos, K Narayanappa, B Mitzkus, M Bethge, FA Wichmann, ...
Oral @ Shared Visual Representations in Humans & Machines Workshop (NeurIPS …, 2020
312020
Partial success in closing the gap between human and machine vision
R Geirhos, K Narayanappa, B Mitzkus, T Thieringer, M Bethge, ...
Oral @ Advances in Neural Information Processing Systems 34 (NeurIPS 2021), 2021
302021
Methods and measurements to compare men against machines
FA Wichmann, DHJ Janssen, R Geirhos, G Aguilar, HH Schütt, ...
Electronic Imaging 2017 (14), 36-45, 2017
112017
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 (ICLR 2021), 2020
9*2020
Trivial or impossible--dichotomous data difficulty masks model differences (on ImageNet and beyond)
K Meding, LMS Buschoff, R Geirhos, FA Wichmann
International Conference on Learning Representations (ICLR 2022), 2021
7*2021
Comparison-Based Framework for Psychophysics: Lab versus Crowdsourcing
S Haghiri, P Rubisch, R Geirhos, F Wichmann, U von Luxburg
arXiv preprint arXiv:1905.07234, 2019
52019
Shortcuts: Neural networks love to cheat
JH Jacobsen, R Geirhos, C Michaelis
The Gradient, 2020
32020
Beyond neural scaling laws: beating power law scaling via data pruning
B Sorscher, R Geirhos, S Shekhar, S Ganguli, AS Morcos
Advances in Neural Information Processing Systems 35 (NeurIPS 2022), 2022
22022
How Well do Feature Visualizations Support Causal Understanding of CNN Activations?
RS Zimmermann, J Borowski, R Geirhos, M Bethge, TSA Wallis, ...
Spotlight @ Advances in Neural Information Processing Systems 34 (NeurIPS 2021), 2021
22021
Of human observers and deep neural networks: A detailed psychophysical comparison
R Geirhos, D Jannsen, H Schütt, M Bethge, FA Wichmann
17th Annual Meeting of the Vision Sciences Society (VSS 2017), 806-806, 2017
22017
The developmental trajectory of object recognition robustness: comparing children, adults, and CNNs
LS Huber, R Geirhos, FA Wichmann
Oral @ 21st Annual Meeting of the Vision Sciences Society (VSS 2021), 1967, 2021
12021
Unintended cue learning: Lessons for deep learning from experimental psychology
R Geirhos, JH Jacobsen, C Michaelis, R Zemel, W Brendel, M Bethge, ...
20th Annual Meeting of the Vision Sciences Society (VSS 2020), 652-652, 2020
12020
The developmental trajectory of object recognition robustness: children are like small adults but unlike big deep neural networks
LS Huber, R Geirhos, FA Wichmann
arXiv preprint arXiv:2205.10144, 2022
2022
To err is human? A functional comparison of human and machine decision-making
R Geirhos
Universität Tübingen, 2022
2022
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