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Umut Güçlü
Umut Güçlü
Principal Investigator, Donders Institute for Brain, Cognition and Behaviour
Verified email at donders.ru.nl - Homepage
Title
Cited by
Cited by
Year
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
10072015
Explainable and Interpretable Models in Computer Vision and Machine Learning
H Escalante, S Escalera, I Guyon, X Baró, Y Güçlütürk, U Güçlü, ...
Springer 2, 2, 2018
860*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
1692018
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
1372015
Modeling the dynamics of human brain activity with recurrent neural networks
U Güçlü, M van Gerven
Frontiers in Computational Neuroscience 11, 7, 2017
1292017
Inpainting and Denoising Challenges
S Escalera, S Ayache, J Wan, M Madadi, U Güçlü, X Baró
Springer, 2019
124*2019
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
1202019
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
1202017
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
1142020
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
1022016
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
85*2017
Convolutional sketch inversion
Y Güçlütürk, U Güçlü, R van Lier, M van Gerven
European Conference on Computer Vision Workshops, 2016
802016
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
682017
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
592014
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
582017
Brains on beats
U Güçlü, J Thielen, M Hanke, M van Gerven
Neural Information Processing Systems, 2016
562016
Wasserstein variational inference
L Ambrogioni, U Güçlü, Y Güçlütürk, M Hinne, M van Gerven, E Maris
Neural Information Processing Systems, 2018
482018
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
472010
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
462017
End-to-end neural system identification with neural information flow
K Seeliger, L Ambrogioni, Y Güçlütürk, L van den Bulk, U Güçlü, ...
PLOS Computational Biology 17 (2), e1008558, 2021
382021
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