Citations: 664; h-index: 11; i10-index: 13.

Preprint

• Ambrogioni, L., Güçlü, U., Güçlütürk, Y., & van Gerven, M. (2018). Wasserstein variational gradient descent: From semi-discrete optimal transport to ensemble variational inference. arXiv preprint arXiv:1811.02827 [stat.ML]. URL
• Ambrogioni, L., Ebel, P., Hinne, M., Güçlü, U., van Gerven, M., & Maris, E. (2018). Semi-analytic nonparametric Bayesian inference for spike-spike neuronal connectivity. bioRxiv, 340489. URL
• Ambrogioni, L., Güçlü, U., Berezutskaya, J., van den Borne, E., Güçlütürk, Y., Hinne, M., Maris, E., & van Gerven, M. (2018). Forward amortized inference for likelihood-free variational marginalization. arXiv preprint arXiv:1805.11542 [stat.ML]. URL
• Jacques Junior, J., Güçlütürk, Y., Pérez, M., Güçlü, U., Andujar, C., Baró, X., Escalante, H., Guyon, I., van Gerven, M., van Lier, R., & others (2018). First Impressions: A survey on computer vision-based apparent personality trait analysis. arXiv preprint arXiv:1804.08046 [cs.CV]. URL
• Escalante, H., Kaya, H., Salah, A., Escalera, S., Güçlütürk, Y., Güçlü, U., Baró, X., Guyon, I., Junior, J., Madadi, M., & others (2018). Explaining first impressions: Modeling, recognizing, and explaining apparent personality from videos. arXiv preprint arXiv:1802.00745 [cs.CV]. URL
• Güçlü, U.*, Güçlütürk, Y.*, Madadi, M., Escalera, S., Baró, X., González, J., van Lier, R., & van Gerven, M. (2017). End-to-end semantic face segmentation with conditional random fields as convolutional, recurrent and adversarial networks. arXiv preprint arXiv:1703.03305 [cs.CV]. (*equal contribution) URL
• Ambrogioni, L., Güçlü, U., Maris, E., & van Gerven, M. (2017). Estimating nonlinear dynamics with the ConvNet smoother. arXiv preprint arXiv:1702.05243 [stat.ML]. URL
• Ambrogioni, L., Güçlü, U., van Gerven, M., & Maris, E. (2017). The kernel mixture network: A nonparametric method for conditional density estimation of continuous random variables. arXiv preprint arXiv:1705.07111 [stat.ML]. URL

Journal

• Seeliger, K., Güçlü, U., Ambrogioni, L., Güçlütürk, Y., & van Gerven, M. (2018). Generative adversarial networks for reconstructing natural images from brain activity. NeuroImage, 181, 775–785. URL
• Güçlütürk, Y., Güçlü, U., van Gerven, M., & van Lier, R. (2018). Representations of naturalistic stimulus complexity in early and associative visual and auditory cortices. Scientific Reports, 8, 3439. URL
• Güçlütürk, Y., Güçlü, U., Baró, X., Escalante, H., Guyon, I., Escalera, S., van Gerven, M., & van Lier, R. (2017). Multimodal first impression analysis with deep residual networks. IEEE Transactions on Affective Computing, 9(3), 316–329. URL
• Berezutskaya, J., Freudenburg, Z., Güçlü, U., van Gerven, M., & Ramsey, N. (2017). Neural tuning to low-level features of speech throughout the perisylvian cortex. The Journal of Neuroscience, 37(33), 7906–7920. URL
• Seeliger, K., Fritsche, M., Güçlü, U., Schoenmakers, S., Schoffelen, J., Bosch, S., & van Gerven, M. (2017). Convolutional neural network-based encoding and decoding of visual object recognition in space and time. NeuroImage, 180(Part A), 253–266. URL
• Güçlü, U., & van Gerven, M. (2017). Modeling the dynamics of human brain activity with recurrent neural networks. Frontiers in Computational Neuroscience, 11, 7. URL
• Güçlü, U., & van Gerven, M. (2015). Increasingly complex representations of natural movies across the dorsal stream are shared between subjects. NeuroImage, 145(Part B), 329–336. URL
• Güçlü, U., & van Gerven, M. (2015). Deep neural networks reveal a gradient in the complexity of neural representations across the ventral stream. The Journal of Neuroscience, 35(27), 10005–10014. URL
• Schoenmakers, S., Güçlü, U., van Gerven, M., & Heskes, T. (2015). Gaussian mixture models and semantic gating improve reconstructions from human brain activity. Frontiers in Computational Neuroscience, 8, 173. URL
• Güçlü, U., & van Gerven, M. (2014). Unsupervised feature learning improves prediction of human brain activity in response to natural images. PLOS Computational Biology, 10(8), e1003724. (best thesis award by Radboud University; best poster award by Donders Institute for Brain, Cognition and Behaviour) URL

Conference

• Ambrogioni, L.*, Güçlü, U.*, Güçlütürk, Y., Hinne, M., van Gerven, M., & Maris, E. (2018). Wasserstein variational inference. In Neural Information Processing Systems. (*equal contribution) URL
• Güçlütürk, Y.*, Güçlü, U.*, Seeliger, K., Bosch, S., van Lier, R., & van Gerven, M. (2017). Reconstructing perceived faces from brain activations with deep adversarial neural decoding. In Neural Information Processing Systems. (*equal contribution; best poster award by Donders Institute for Brain, Cognition and Behaviour) URL
• Ambrogioni, L., Berezutskaya, J., Güçlü, U., van den Borne, E., Güçlütürk, Y., van Gerven, M., & Maris, E. (2017). Bayesian model ensembling using meta-trained recurrent neural networks. In Neural Information Processing Systems Workshops. URL
• Güçlü, U., Güçlütürk, Y., Ambrogioni, L., Maris, E., van Lier, R., & van Gerven, M. (2017). Algorithmic composition of polyphonic music with the WaveCRF. In Neural Information Processing Systems Workshops. URL
• Güçlütürk, Y., Güçlü, U., Pérez, M., Escalante, H., Baró, X., Guyon, I., Andujar, C., Jacques Junior, J., Madadi, M., Escalera, S., & others (2017). Visualizing apparent personality analysis with deep residual networks. In International Conference on Computer Vision Workshops. URL
• Berezutskaya, J., Freudenburg, Z., Ramsey, N., Güçlü, U., & van Gerven, M. (2017). Modeling brain responses to perceived speech with LSTM networks. In Benelux Conference on Machine Learning. URL
• Escalante, H., Guyon, I., Escalera, S., Jacques Junior, J., Madadi, M., Baró, X., Ayache, S., Viegas, E., Güçlütürk, Y., Güçlü, U., & others (2017). Design of an explainable machine learning challenge for video interviews. In International Joint Conference on Neural Networks. URL
• Güçlü, U., Thielen, J., Hanke, M., & van Gerven, M. (2016). Brains on beats. In Neural Information Processing Systems. URL
• Güçlütürk, Y.*, Güçlü, U.*, van Lier, R., & van Gerven, M. (2016). Convolutional sketch inversion. In European Conference on Computer Vision Workshops. (*equal contribution) URL
• Güçlütürk, Y., Güçlü, U., van Gerven, M., & van Lier, R. (2016). Deep impression: Audiovisual deep residual networks for multimodal apparent personality trait recognition. In European Conference on Computer Vision Workshops. URL
• Güçlü, U., & van Gerven, M. (2015). Semantic vector space models predict neural responses to complex visual stimuli. In Neural Information Processing Systems Workshops. URL
• Güçlü, U., & van Gerven, M. (2013). Unsupervised learning of features for Bayesian decoding in functional magnetic resonance imaging. In Benelux Conference on Machine Learning. URL
• Güçlü, U., Güçlütürk, Y., & Loo, C. (2011). Evaluation of fractal dimension estimation methods for feature extraction in motor imagery based brain computer interface. Procedia Computer Science, 3(Supplement C), 589–594. URL
• Güçlütürk, Y., Güçlü, U., & Samraj, A. (2010). An online single trial analysis of the P300 event related potential for the disabled. In Convention of Electrical & Electronics Engineers in Israel. URL
• Güçlü, U., Güçlütürk, Y., & Samraj, A. (2010). A novel approach to improve the performance of the P300 speller paradigm. In International Conference on Systems, Man and Cybernetics. URL

Demo

• Escalera, S., Guyon, I., Chen, B., Quintana, M., Güçlü, U., Güçlütürk, Y., Baró, X., van Lier, R., Andujar, C., van Gerven, M., Boser, B., and Wang, L. (2016). Biometric applications of CNNs: Get a job at “Impending Technologies”!. In Neural Information Processing Systems. URL

Chapter

• Güçlü, U., & van Gerven, M. (2017). Probing human brain function with artificial neural networks. In A. Moustafa (Ed.), Computational Models of Brain and Behavior (pp. 413-423). Hoboken, NJ: Wiley-Blackwell. URL

Book

• Escalante, H., Escalera, S., Guyon, I., Baró, X., Güçlütürk, Y., Güçlü, U., & van Gerven, M. (2018). Explainable and interpretable models in computer vision and machine learning. Berlin/Heidelberg, Germany: Springer Science+Business Media. URL