| Generalisation in humans and deep neural networks R Geirhos, CRM Temme, J Rauber, HH Schütt, M Bethge, FA Wichmann Advances in neural information processing systems 31, 2018 | 662* | 2018 |
| Painfree and accurate Bayesian estimation of psychometric functions for (potentially) overdispersed data HH Schütt, S Harmeling, JH Macke, FA Wichmann Vision research 122, 105-123, 2016 | 293* | 2016 |
| An image-computable psychophysical spatial vision model HH Schütt, FA Wichmann Journal of vision 17 (12), 12-12, 2017 | 35 | 2017 |
| Likelihood-based parameter estimation and comparison of dynamical cognitive models. HH Schütt, LOM Rothkegel, HA Trukenbrod, S Reich, FA Wichmann, ... Psychological review 124 (4), 505, 2017 | 35 | 2017 |
| Disentangling bottom-up versus top-down and low-level versus high-level influences on eye movements over time HH Schütt, LOM Rothkegel, HA Trukenbrod, R Engbert, FA Wichmann Journal of vision 19 (3), 1-1, 2019 | 32 | 2019 |
| Temporal evolution of the central fixation bias in scene viewing LOM Rothkegel, HA Trukenbrod, HH Schütt, FA Wichmann, R Engbert Journal of vision 17 (13), 3-3, 2017 | 28 | 2017 |
| Comparing representational geometries using whitened unbiased-distance-matrix similarity J Diedrichsen, E Berlot, M Mur, HH Schütt, M Shahbazi, N Kriegeskorte arXiv preprint arXiv:2007.02789, 2020 | 21* | 2020 |
| Influence of initial fixation position in scene viewing LOM Rothkegel, HA Trukenbrod, HH Schütt, FA Wichmann, R Engbert Vision research 129, 33-49, 2016 | 17 | 2016 |
| Searchers adjust their eye-movement dynamics to target characteristics in natural scenes LOM Rothkegel, HH Schütt, HA Trukenbrod, FA Wichmann, R Engbert Scientific reports 9 (1), 1-12, 2019 | 15 | 2019 |
| Comparing deep neural networks against humans: Object recognition when the signal gets weaker. arXiv 2017 R Geirhos, DHJ Janssen, HH Schütt, J Rauber, M Bethge, FA Wichmann arXiv preprint arXiv:1706.06969, 2018 | 14 | 2018 |
| 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 | 13 | 2017 |
| Deep neural models for color classification and color constancy A Flachot, A Akbarinia, HH Schütt, RW Fleming, FA Wichmann, ... Journal of Vision 22 (4), 17-17, 2022 | 6 | 2022 |
| Perception of light source distance from shading patterns HH Schuett, F Baier, RW Fleming Journal of Vision 16 (3), 9-9, 2016 | 5 | 2016 |
| Comparing deep neural networks against humans: object recognition when the signal gets weaker (2017) R Geirhos, DHJ Janssen, HH Schütt, J Rauber, M Bethge, FA Wichmann arXiv preprint arXiv:1706.06969, 0 | 5 | |
| Statistical inference on representational geometries HH Schütt, AD Kipnis, J Diedrichsen, N Kriegeskorte arXiv preprint arXiv:2112.09200, 2021 | 2 | 2021 |
| Color constancy in deep neural networks AC Flachot, HH Schuett, RW Fleming, F Wichmann, KR Gegenfurtner Journal of Vision 19 (10), 298-298, 2019 | 2 | 2019 |
| Of human observers and deep neural networks: A detailed psychophysical comparison R Geirhos, D Janssen, H Schütt, M Bethge, F Wichmann Journal of Vision 17 (10), 806-806, 2017 | 2 | 2017 |
| Distinguishing representational geometries with controversial stimuli: Bayesian experimental design and its application to face dissimilarity judgments T Golan, W Guo, HH Schütt, N Kriegeskorte arXiv preprint arXiv:2211.15053, 2022 | 1 | 2022 |
| Reward prediction error neurons implement an efficient code for reward D Kim, HH Schuett, WJ Ma bioRxiv, 2022.11. 03.515104, 2022 | 1 | 2022 |
| Point estimate observers: A new class of models for perceptual decision making H Schütt, AH Yoo, J Calder-Travis, WJ Ma PsyArXiv, 2021 | 1 | 2021 |
Felix WichmannEberhard Karls Universität TübingenVerified email at uni-tuebingen.de
