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Browsing by Author "Güçlü, U."
Now showing items 1-32 of 32
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Current advances in neural decoding 2019, Part of book or chapter of book (Samek, W.; Montavon, G.; Vedaldi, A. (ed.), Explainable AI: Interpreting, explaining and visualizing deep learning, pp. 379-394) -
Forward amortized inference for likelihood-free variational marginalization Ambrogioni, L. ; Güçlü, U. ; Berezutskaya, Y. ; Borne, E.W.P. van den; Güçlütürk, Y. ; Hinne, M. ; Maris, E.G.G. ; Gerven, M.A.J. van2019, Article in monograph or in proceedings (Chaudhuri, K.; Sugiyama, M. (ed.), Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics (AISTATS) 2019, pp. 777-786)
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SpikeCaKe: Semi-analytic nonparametric Bayesian inference for spike-spike neuronal connectivity Ambrogioni, L. ; Ebel, P.W.; Hinne, M. ; Güçlü, U. ; Gerven, M.A.J. van ; Maris, E.G.G.2019, Article in monograph or in proceedings (Chaudhuri, K.; Sugiyama, M. (ed.), Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics (AISTATS) 2019, pp. 787-795)
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Temporal factorization of 3D convolutional kernels 2019, Article in monograph or in proceedings (Beuls, K.; Bogaerts, B.; Bontempi, G. (ed.), Proceedings of the 31st Benelux Conference on Artificial Intelligence (BNAIC 2019) and the 28th Belgian Dutch Conference on Machine Learning (Benelearn 2019), pp. 1-9)
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Neural information flow: Learning neural information processing systems from brain activity 2019, Article in monograph or in proceedings (2019 Conference on Cognitive Computational Neuroscience, pp. 717-720)
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ChaLearn Looking at People: Inpainting and denoising challenges Escalera, S.; Soler, M.; Ayache, S.; Güçlü, U. ; Wan, J.; Madadi, M.; Baró, X.; Escalante, H.J.; Guyon, I.2019, Article in monograph or in proceedings (Escalera, S.; Ayache, S.; Wan, J. (ed.), Inpainting and denoising challenges: Conference proceedings, pp. 23-44)
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Inpainting and denoising challenges: Conference proceedings Escalera, S.; Ayache, S.; Wan, J.; Madadi, M.; Güçlü, U. ; Baró, X.2019, Book editorial
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Simulating neuroprosthetic vision for emotion recognition Bollen, C.J.M.; Güçlü, U. ; Wezel, R.J.A. van ; Gerven, M.A.J. van ; Güçlütürk, Y.2019, Article in monograph or in proceedings (2019 8th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW), pp. 85-87)
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Explainable and interpretable models in computer vision and machine learning Escalante, H.J.; Escalera, S.; Guyon, I.; Baró, X.; Güçlütürk, Y. ; Güçlü, U. ; Gerven, M.A.J. van2018, Book editorial
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Multimodal first impression analysis with deep residual networks Güçlütürk, Y. ; Güçlü, U. ; Baró, X.; Escalante, H.J.; Guyon, I.; Escalera, S.; Gerven, M.A.J. van ; Lier, R.J. van2018, Article / Letter to editor (IEEE Transactions on Affective Computing, vol. 9, iss. 3, (2018), pp. 316-329)
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Representations of naturalistic stimulus complexity in early and associative visual and auditory cortices 2018, Article / Letter to editor (Scientific Reports, vol. 8, (2018), article 3439)
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Convolutional neural network-based encoding and decoding of visual object recognition in space and time Seeliger, K. ; Fritsche, M. ; Güçlü, U. ; Schoenmakers, S. ; Schoffelen, J.M. ; Bosch, S.E. ; Gerven, M.A.J. van2018, Article / Letter to editor (NeuroImage, vol. 180, iss. Part A, (2018), pp. 253-266) -
Generative adversarial networks for reconstructing natural images from brain activity 2018, Article / Letter to editor (NeuroImage, vol. 181, (2018), pp. 775-785)
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Wasserstein variational inference 2018, Article in monograph or in proceedings (Bengio, S.; Wallach, H.M.; Larochelle, H. (ed.), Proceedings of the 32nd International Conference on Neural Information Processing Systems, pp. 2478-2487)
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Modeling brain responses to perceived speech with LSTM networks Berezutskaya, Y. ; Freudenburg, Z.V.; Ramsey, N.F.; Güçlü, U. ; Gerven, M.A.J. van2017, Article in monograph or in proceedings (Duivesteijn, W.; Pechenizkiy, M.; Fletcher, G.H.L. (ed.), Benelearn 2017: Proceedings of the Twenty-Sixth Benelux Conference on Machine Learning, Technische Universiteit Eindhoven, 9-10 June 2017, pp. 149-153)
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Increasingly complex representations of natural movies across the dorsal stream are shared between subjects 2017, Article / Letter to editor (NeuroImage, vol. 145, iss. Part B, (2017), pp. 329-336)
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Neural tuning to low-level features of speech throughout the perisylvian cortex Berezutskaya, Y. ; Freudenburg, Z.V.; Güçlü, U. ; Gerven, M.A.J. van ; Ramsey, N.F.2017, Article / Letter to editor (The Journal of Neuroscience, vol. 37, iss. 33, (2017), pp. 7906-7920)
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Probing human brain function with artificial neural networks 2017, Part of book or chapter of book (Moustafa, A.A. (ed.), Computational models of brain and behavior, pp. 413-423)
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Modeling the dynamics of human brain activity with recurrent neural networks 2017, Article / Letter to editor (Frontiers in Computational Neuroscience, vol. 11, (2017), article 7)
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Visualizing apparent personality analysis with deep residual networks Güçlütürk, Y. ; Güçlü, U. ; Pérez, M.; Escalante, H.J.; Baró, X.; Guyon, I.; Andujar, C.; Jacques, J.; Madadi, M.; Escalera, S.; Gerven, M.A.J. van ; Lier, R.J. van et al.2017, Article in monograph or in proceedings (2017 IEEE International Conference on Computer Vision (ICCV), pp. 3101-3109)
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Design of an explainable machine learning challenge for video interviews Escalante, H.J.; Guyon, I.; Escalera, S.; Jacques, J.; Madadi, M.; Baró, X.; Ayache, S.; Viegas, E.; Güçlütürk, Y. ; Güçlü, U. ; Gerven, M.A.J. van ; Lier, R.J. van et al.2017, Article in monograph or in proceedings (2017 International Joint Conference on Neural Networks (IJCNN), pp. 3688-3695)
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Algorithmic composition of polyphonic music with the WaveCRF 2017, Article in monograph or in proceedings (2017 Neural Information Processing Systems (NIPS): Machine Learning for Creativity and Design Workshop (December 8, 2017), pp. 1-3)
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Bayesian model ensembling using meta-trained recurrent neural networks Ambrogioni, L. ; Berezutskaya, Y. ; Güçlü, U. ; Borne, E.W.P. van den; Güçlütürk, Y. ; Gerven, M.A.J. van ; Maris, E.G.G.2017, Article in monograph or in proceedings (Workshop on Meta-Learning (MetaLearn 2017) - Neural Information Processing Systems (NIPS 2017), pp. 1-5)
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Reconstructing perceived faces from brain activations with deep adversarial neural decoding 2017, Article in monograph or in proceedings (Guyon, I.; Luxburg, U.V.; Bengio, S. (ed.), Advances in Neural Information Processing Systems 30 (NIPS 2017) Pre-Proceedings, pp. 4249-4260)
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Brains on beats Güçlü, U. ; Thielen, J. ; Hanke, M.; Gerven, M.A.J. van2016, Article in monograph or in proceedings (Lee, D.D.; Sugiyama, M.; Luxburg, U.V. (ed.), Advances in Neural Information Processing Systems 29 (NIPS 2016), pp. 1-9)
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Deep impression: Audiovisual deep residual networks for multimodal apparent personality trait recognition 2016, Article in monograph or in proceedings (Hua, G.; Jégou, H. (ed.), Computer Vision - ECCV 2016 Workshops, Proceedings, pp. 349-358)
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Convolutional sketch inversion 2016, Article / Letter to editor (Lecture Notes in Computer Science, vol. 9913, (2016), pp. 810-814)
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Deep neural networks reveal a gradient in the complexity of neural representations across the ventral stream 2015, Article / Letter to editor (The Journal of Neuroscience, vol. 35, iss. 27, (2015), pp. 10005-10014)
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Gaussian mixture models and semantic gating improve reconstructions from human brain activity 2015, Article / Letter to editor (Frontiers in Computational Neuroscience, vol. 8, (2015), article 173)
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Unsupervised feature learning improves prediction of human brain activity in response to natural images 2014, Article / Letter to editor (Plos Computational Biology, vol. 10, iss. 8, (2014), article e1003724)
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Gaussian mixture models improve fMRI-based image reconstruction 2014, Part of book or chapter of book (PRNI 2014: 2014 International Workshop on Pattern Recognition in Neuroimaging, Tübingen, June 4-6 2014 : Proceedings, pp. 1-4)
Now showing items 1-32 of 32
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