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  1. 1
    Physiologically informed dynamic causal modeling of fMRI data

    Physiologically informed dynamic causal modeling of fMRI data 由 Martin Havlíček, Alard Roebroeck, Karl Friston, Anna Gardumi, Dimo Ivanov, Kâmil Uludaǧ

    出版 2015
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  2. 2
    Bayesian hierarchical grouping: Perceptual grouping as mixture estimation.

    Bayesian hierarchical grouping: Perceptual grouping as mixture estimation. 由 Vicky Froyen, Jacob Feldman, Manish Singh

    出版 2015
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  3. 3
    Towards Biologically Plausible Deep Learning

    Towards Biologically Plausible Deep Learning 由 Yoshua Bengio, Dong-Hyun Lee, Jörg Bornschein, Zhouhan Lin

    出版 2015
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  4. 4
    Derived Relational Networks and Control by Novel Instructions: A Possible Model of Generative Verbal Responding

    Derived Relational Networks and Control by Novel Instructions: A Possible Model of Generative Verbal Responding 由 Denis O’Hora, Dermot Barnes‐Holmes, Bryan Roche, Paul M. Smeets

    出版 2004
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  5. 5
    GERV: a statistical method for generative evaluation of regulatory variants for transcription factor binding

    GERV: a statistical method for generative evaluation of regulatory variants for transcription factor binding 由 Haoyang Zeng, Tatsunori Hashimoto, Daniel Kang, David K. Gifford

    出版 2015
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  6. 6
    Unifying account of visual motion and position perception

    Unifying account of visual motion and position perception 由 Oh‐Sang Kwon, Duje Tadin, David C. Knill

    出版 2015
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  7. 7
    Generative Embedding for Model-Based Classification of fMRI Data

    Generative Embedding for Model-Based Classification of fMRI Data 由 Kay H. Brodersen, Thomas M. Schofield, Alexander Leff, Cheng Soon Ong, Ekaterina I. Lomakina, Joachim M. Buhmann, Klaas Ε. Stephan

    出版 2011
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  8. 8
    Charles Bonnet Syndrome: Evidence for a Generative Model in the Cortex?

    Charles Bonnet Syndrome: Evidence for a Generative Model in the Cortex? 由 David Reichert, Peggy Seriès, Amos Storkey

    出版 2013
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  9. 9
    Hierarchical Models in the Brain

    Hierarchical Models in the Brain 由 Karl Friston

    出版 2008
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  10. 10
    Dopamine, Affordance and Active Inference

    Dopamine, Affordance and Active Inference 由 Karl Friston, Tamara Shiner, Thomas H. B. FitzGerald, Joseph M. Galea, Rick A. Adams, Harriet R. Brown, Raymond J. Dolan, Rosalyn Moran, Klaas Ε. Stephan, Sven Bestmann

    出版 2012
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  11. 11
    A probabilistic generative model for GO enrichment analysis

    A probabilistic generative model for GO enrichment analysis 由 Yong Lu, Roni Rosenfeld, Itamar Simon, Gerard J. Nau, Ziv Bar‐Joseph

    出版 2008
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  12. 12
    Generative models of rich clubs in Hebbian neuronal networks and large-scale human brain networks

    Generative models of rich clubs in Hebbian neuronal networks and large-scale human brain networks 由 Petra E. Vértes, Aaron Alexander‐Bloch, Edward T. Bullmore

    出版 2014
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  13. 13
    Generative constraints on image cues for perceived gloss

    Generative constraints on image cues for perceived gloss 由 P. Marlow, Barton L. Anderson

    出版 2013
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  14. 14
    Causal inference of asynchronous audiovisual speech

    Causal inference of asynchronous audiovisual speech 由 John F. Magnotti, Wei Ji, Michael S. Beauchamp

    出版 2013
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  15. 15
    What Is Optimal about Motor Control?

    What Is Optimal about Motor Control? 由 Karl Friston

    出版 2011
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    Carta
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  16. 16
    Bayesian Computation Emerges in Generic Cortical Microcircuits through Spike-Timing-Dependent Plasticity

    Bayesian Computation Emerges in Generic Cortical Microcircuits through Spike-Timing-Dependent Plasticity 由 Bernhard Nessler, Michael Pfeiffer, Lars Buesing, Wolfgang Maass

    出版 2013
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  17. 17
    Dissecting psychiatric spectrum disorders by generative embedding

    Dissecting psychiatric spectrum disorders by generative embedding 由 Kay H. Brodersen, Lorenz Deserno, Florian Schlagenhauf, Zhihao Lin, W.D. Penny, Joachim M. Buhmann, Klaas Ε. Stephan

    出版 2013
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  18. 18
    Nonlinear local electrovascular coupling. I: A theoretical model

    Nonlinear local electrovascular coupling. I: A theoretical model 由 Jorge Riera, Xiaohong Wan, Juan Carlos Jiménez, Ryuta Kawashima

    出版 2006
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  19. 19
    A Parametric Empirical Bayesian framework for fMRI‐constrained MEG/EEG source reconstruction

    A Parametric Empirical Bayesian framework for fMRI‐constrained MEG/EEG source reconstruction 由 Richard N. Henson, Guillaume Flandin, Karl Friston, Jérémie Mattout

    出版 2010
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  20. 20
    Dynamic causal modelling for functional near-infrared spectroscopy

    Dynamic causal modelling for functional near-infrared spectroscopy 由 Sungho Tak, Agnieszka Kempny, Karl Friston, Alexander Leff, W.D. Penny

    出版 2015
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