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Browsing by Author "Gerven, M.A.J. van"
Now showing items 1-50 of 162
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Deep learning improves automated rodent behavior recognition within a specific experimental setup Dam, E.A. van ; Noldus, L.P.J.J.; Gerven, M.A.J. van2020, Article / Letter to editor (Journal of Neuroscience Methods, vol. 332, (2020), article 108536) -
Validation of structural brain connectivity networks: The impact of scanning parameters Ambrosen, K.S.; Eskildsen, S.F.; Hinne, M. ; Krug, K.; Lundell, H.; Schmidt, M.N.; Gerven, M.A.J. van ; Morup, M.; Dyrby, T.B.2020, Article / Letter to editor (NeuroImage, vol. 204, (2020), article 116207) -
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)
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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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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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Task-dependent attention allocation through uncertainty minimization in deep recurrent generative models Standvoss, K.; Quax, S.C. ; Gerven, M.A.J. van2019, Article in monograph or in proceedings (2019 Conference on Cognitive Computational Neuroscience, pp. 1022-1025)
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Mind the eye: Confounding eye movements in cognitive neuroscience 2019, Article / Letter to editor (Perception, vol. 48, iss. Suppl. 2, (2019), pp. 86)
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Evidence for confounding eye movements under attempted fixation and active viewing in cognitive neuroscience 2019, Article / Letter to editor (Scientific Reports, vol. 9, (2019), article 17456)
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Shared neural mechanisms of visual perception and imagery 2019, Article / Letter to editor (Trends in Cognitive Sciences, vol. 23, iss. 5, (2019), pp. 423-434)
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Eye movements explain decodability during perception and cued attention in MEG Quax, S.C. ; Dijkstra, N. ; Staveren, M.J. van; Bosch, S.E. ; Gerven, M.A.J. van2019, Article / Letter to editor (NeuroImage, vol. 195, (2019), pp. 444-453)
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Neuroimaging findings on amodal completion: A review 2019, Article / Letter to editor (I-Perception, vol. 10, iss. 2, (2019), article 2041669519840047)
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Between-subject variability in the influence of mental imagery on conscious perception 2019, Article / Letter to editor (Scientific Reports, vol. 9, (2019), article 15658)
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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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Emotion recognition with simulated phosphene vision Bollen, C.J.M.; Wezel, R.J.A. van ; Gerven, M.A.J. van ; Güçlütürk, Y.2019, Article in monograph or in proceedings (Liu, X.; Min, R.; McDaniel, T. (ed.), MAHCI '19: Proceedings of the 2nd Workshop on Multimedia for Accessible Human Computer Interfaces, pp. 1-8)
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Eye movement effects in MEG Quax, S.C. ; Dijkstra, N. ; Staveren, M.J. van; Bosch, S.E. ; Gerven, M.A.J. van2019, Dataset
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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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Modulation of early visual processing alleviates capacity limits in solving multiple tasks 2019, Article in monograph or in proceedings (2019 Conference on Cognitive Computational Neuroscience, pp. 226-229)
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Explanation methods in deep learning: Users, values, concerns and challenges 2018, Part of book or chapter of book (Escalante, H.J.; Escalera, S.; Guyon, I. (ed.), Explainable and interpretable models in computer vision and machine learning, pp. 19-36)
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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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Emergent mechanisms of evidence integration in recurrent neural networks 2018, Article / Letter to editor (PLoS One, vol. 13, iss. 10, (2018), article e0205676)
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New fMRI methods for the study of language 2018, Part of book or chapter of book (Rueschemeyer, S.A.; Gaskell, M.G. (ed.), The Oxford handbook of psycholinguistics (2nd ed.), pp. 975-991) -
Differential temporal dynamics during visual imagery and perception 2018, Article / Letter to editor (Elife, vol. 7, (2018), article e33904)
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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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No evidence for confounding orientation-dependent fixational eye movements under baseline conditions 2018, Article / Letter to editor (Scientific Reports, vol. 8, (2018), article 11644)
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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)
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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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The functional role of cue-driven feature-based feedback in object recognition 2018, Article in monograph or in proceedings (Proceedings 2018 Conference on Cognitive Computational Neuroscience, pp. 1-4)
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Parkinsonian rest tremor can be detected accurately based on neuronal oscillations recorded from the subthalamic nucleus Hirschmann, J. ; Schoffelen, J.M. ; Schnitzler, A.; Gerven, M.A.J. van2017, Article / Letter to editor (Clinical Neurophysiology, vol. 128, iss. 10, (2017), pp. 2029-2036)
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Vividness of visual imagery depends on the neural overlap with perception in visual areas 2017, Article / Letter to editor (The Journal of Neuroscience, vol. 37, iss. 5, (2017), pp. 1367-1373)
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A primer on encoding models in sensory neuroscience 2017, Article / Letter to editor (Journal of Mathematical Psychology, vol. 76, iss. Part B, (2017), pp. 172-183)
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Computational foundations of natural intelligence 2017, Article / Letter to editor (Frontiers in Computational Neuroscience, vol. 11, (2017), article 112)
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Predicting and visualizing psychological attributions with a deep neural network Grant, E.; Sahm, S.; Zabihi, M. ; Gerven, M.A.J. van2017, Article in monograph or in proceedings (Pattern Recognition (ICPR), 2016 23rd International Conference on Pattern Recognition (ICPR), pp. 1-6)
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Bayesian estimation of directed functional coupling from brain recordings Benozzo, D.; Jylänki, P.P. ; Olivetti, E.; Avesani, P.; Gerven, M.A.J. van2017, Article / Letter to editor (PLoS One, vol. 12, iss. 5, (2017), article e0177359)
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The missing link: Predicting connectomes from noisy and partially observed tract tracing data Hinne, M. ; Meijers, A.; Bakker, R. ; Tiesinga, P.H.E.; Morup, M.; Gerven, M.A.J. van2017, Article / Letter to editor (Plos Computational Biology, vol. 13, iss. 1, (2017), article e1005374)
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Correction: The missing link: Predicting connectomes from noisy and partially observed tract tracing data Hinne, M. ; Meijers, A.; Bakker, R. ; Tiesinga, P.H.E.; Morup, M.; Gerven, M.A.J. van2017, Article / Letter to editor (Plos Computational Biology, vol. 13, iss. 4, (2017), article e1005478)
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Editorial: Artificial neural networks as models of neural information processing Gerven, M.A.J. van ; Bohte, S.M.2017, Article / Letter to editor (Frontiers in Computational Neuroscience, vol. 11, (2017), article 114)
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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)
Now showing items 1-50 of 162
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