| Deep neural networks reveal a gradient in the complexity of neural representations across the ventral stream U Güçlü, M van Gerven The Journal of Neuroscience 35 (27), 10005-10014, 2015 | 832 | 2015 |
| Explainable and interpretable models in computer vision and machine learning H Escalante, S Escalera, I Guyon, X Baró, Y Güçlütürk, U Güçlü, ... Springer, 2018 | 652* | 2018 |
| Generative adversarial networks for reconstructing natural images from brain activity K Seeliger, U Güçlü, L Ambrogioni, Y Güçlütürk, M van Gerven NeuroImage 181, 775-785, 2018 | 117 | 2018 |
| Increasingly complex representations of natural movies across the dorsal stream are shared between subjects U Güçlü, M van Gerven NeuroImage 145 (Part B), 329-336, 2015 | 117 | 2015 |
| Modeling the dynamics of human brain activity with recurrent neural networks U Güçlü, M van Gerven Frontiers in Computational Neuroscience 11, 7, 2017 | 112 | 2017 |
| Convolutional neural network-based encoding and decoding of visual object recognition in space and time K Seeliger, M Fritsche, U Güçlü, S Schoenmakers, J Schoffelen, S Bosch, ... NeuroImage 180 (Part A), 253-266, 2017 | 96 | 2017 |
| First impressions: A survey on vision-based apparent personality trait analysis J Jacques Junior, Y Güçlütürk, M Pérez, U Güçlü, C Andujar, X Baró, ... IEEE Transactions on Affective Computing, 2019 | 91 | 2019 |
| Inpainting and Denoising Challenges S Escalera, S Ayache, J Wan, M Madadi, U Güçlü, X Baró Springer, 2019 | 84* | 2019 |
| Deep impression: Audiovisual deep residual networks for multimodal apparent personality trait recognition Y Güçlütürk, U Güçlü, M van Gerven, R van Lier European Conference on Computer Vision Workshops, 2016 | 82 | 2016 |
| Modeling, recognizing, and explaining apparent personality from videos H Escalante, H Kaya, A Salah, S Escalera, Y Güçlütürk, U Güçlü, X Baró, ... IEEE Transactions on Affective Computing, 2020 | 79* | 2020 |
| Convolutional sketch inversion Y Güçlütürk, U Güçlü, R van Lier, M van Gerven European Conference on Computer Vision Workshops, 2016 | 74 | 2016 |
| Reconstructing perceived faces from brain activations with deep adversarial neural decoding Y Güçlütürk, U Güçlü, K Seeliger, S Bosch, R van Lier, M van Gerven Neural Information Processing Systems, 2017 | 71* | 2017 |
| Multimodal first impression analysis with deep residual networks Y Güçlütürk, U Güçlü, X Baró, H Escalante, I Guyon, S Escalera, ... IEEE Transactions on Affective Computing 9 (3), 316-329, 2017 | 60 | 2017 |
| Brains on beats U Güçlü, J Thielen, M Hanke, M van Gerven Neural Information Processing Systems, 2016 | 55 | 2016 |
| Unsupervised feature learning improves prediction of human brain activity in response to natural images U Güçlü, M van Gerven PLOS Computational Biology 10 (8), e1003724, 2014 | 55 | 2014 |
| Evaluation of fractal dimension estimation methods for feature extraction in motor imagery based brain computer interface U Güçlü, Y Güçlütürk, C Loo World Conference on Information Technology, 2010 | 45 | 2010 |
| Design of an explainable machine learning challenge for video interviews H Escalante, I Guyon, S Escalera, J Jacques Junior, M Madadi, X Baró, ... International Joint Conference on Neural Networks, 2017 | 43 | 2017 |
| Wasserstein variational inference L Ambrogioni, U Güçlü, Y Güçlütürk, M Hinne, M van Gerven, E Maris Neural Information Processing Systems, 2018 | 38 | 2018 |
| The kernel mixture network: A nonparametric method for conditional density estimation of continuous random variables L Ambrogioni, U Güçlü, M van Gerven, E Maris arXiv:1705.07111 [stat.ML], 2017 | 31 | 2017 |
| Gaussian mixture models and semantic gating improve reconstructions from human brain activity S Schoenmakers, U Güçlü, M van Gerven, T Heskes Frontiers in Computational Neuroscience 8, 173, 2015 | 31 | 2015 |
Marcel van GervenProfessor of Artificial Cognitive Systems, Donders Institute for Brain, Cognition and BehaviourVerified email at donders.ru.nl
