| Recurrent convolutional neural networks: a better model of biological object recognition CJ Spoerer, P McClure, N Kriegeskorte Frontiers in psychology 8, 1551, 2017 | 99 | 2017 |
| Recurrence is required to capture the representational dynamics of the human visual system TC Kietzmann, CJ Spoerer, LKA Sörensen, RM Cichy, O Hauk, ... Proceedings of the National Academy of Sciences 116 (43), 21854-21863, 2019 | 78* | 2019 |
| Individual differences among deep neural network models J Mehrer, CJ Spoerer, N Kriegeskorte, TC Kietzmann bioRxiv, 2020 | 8 | 2020 |
| Recurrent neural networks can explain flexible trading of speed and accuracy in biological vision CJ Spoerer, TC Kietzmann, J Mehrer, I Charest, N Kriegeskorte PLoS computational biology 16 (10), e1008215, 2020 | 7* | 2020 |
| A computational exploration of complementary learning mechanisms in the primate ventral visual pathway CJ Spoerer, A Eguchi, SM Stringer Vision Research 119, 16-28, 2016 | 5 | 2016 |
| Corrigendum: Recurrent Convolutional Neural Networks: A Better Model of Biological Object Recognition CJ Spoerer, P McClure, N Kriegeskorte Frontiers in psychology 9, 1695, 2018 | 1 | 2018 |
| Recurrent convolutional neural networks as models of biological object recognition C Spoerer University of Cambridge, 2020 | | 2020 |
| Recurrent convolutional neural networks suppress occluders and enhance targets in occluded object recognition CJ Spoerer, N Kriegeskorte Conference on Cognitive Computational Neuroscience, 2017 | | 2017 |
| Representational dynamics in the human ventral stream captured in deep recurrent neural nets TC Kietzmann, CJ Spoerer, L Sörensen, RM Cichy, O Hauk, ... | | |
