| 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 | 2918 | 2019 |
| 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 | 1829 | 2020 |
| 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 | 693 | 2018 |
| 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 | 464 | 2019 |
| Scaling vision transformers to 22 billion parameters M Dehghani, J Djolonga, B Mustafa, P Padlewski, J Heek, J Gilmer, ... Oral @ International Conference on Machine Learning (ICML 2023), 2023 | 340 | 2023 |
| 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 | 304 | 2017 |
| Beyond neural scaling laws: beating power law scaling via data pruning B Sorscher, R Geirhos, S Shekhar, S Ganguli, AS Morcos Outstanding Paper Award @ Advances in Neural Information Processing Systems …, 2022 | 276 | 2022 |
| 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 | 209 | 2021 |
| 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 | 106 | 2020 |
| 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 | 50 | 2020 |
| 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 | 48* | 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 | 36 | 2021 |
| Patch n'Pack: NaViT, a Vision Transformer for any Aspect Ratio and Resolution M Dehghani, B Mustafa, J Djolonga, J Heek, M Minderer, M Caron, ... Advances in Neural Information Processing Systems 36 (NeurIPS 2023), 2023 | 33 | 2023 |
| Are deep neural networks adequate behavioral models of human visual perception? FA Wichmann, R Geirhos Annual Review of Vision Science 9 (1), 501-524, 2023 | 31 | 2023 |
| 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 | 30 | 2021 |
| Getting aligned on representational alignment I Sucholutsky, L Muttenthaler, A Weller, A Peng, A Bobu, B Kim, BC Love, ... arXiv preprint arXiv:2310.13018, 2023 | 26 | 2023 |
| The developmental trajectory of object recognition robustness: Children are like small adults but unlike big deep neural networks LS Huber, R Geirhos, FA Wichmann Journal of Vision 23 (7), 4-4, 2023 | 24* | 2023 |
| Methods and measurements to compare men against machines FA Wichmann, DHJ Janssen, R Geirhos, G Aguilar, HH Schütt, ... Electronic Imaging 29, 36-45, 2017 | 20 | 2017 |
| Intriguing properties of generative classifiers P Jaini, K Clark, R Geirhos Spotlight @ International Conference on Learning Representations (ICLR 2024), 2023 | 19 | 2023 |
| Don't trust your eyes: on the (un) reliability of feature visualizations R Geirhos, RS Zimmermann, B Bilodeau, W Brendel, B Kim International Conference on Learning Representations (ICML 2024), 2024 | 13 | 2024 |
Felix WichmannEberhard Karls Universität Tübingen在 uni-tuebingen.de 的电子邮件经过验证
