Publications

(2019). A hierarchical, multi-layer convolutional sparse coding algorithm based on predictive coding. NeuroFrance 2019, International Conference from the Société des Neurosciences, Marseille, France.

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(2018). ANEMO: Quantitative tools for the ANalysis of Eye MOvements. Grenoble Workshop on Models and Analysis of Eye Movements, Grenoble, France.

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(2017). Efficient learning of sparse image representations using homeostatic regulation. NeuroFrance 2017, International Conference from the Société des Neurosciences, Bordeaux, France.

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(2016). Compensation of oculomotor delays in the visual system's network. Complex Networks: from theory to interdisciplinary applications.

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(2015). Sparse Models for Computer Vision. Biologically Inspired Computer Vision.

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(2015). Introduction. Biologically Inspired Computer Vision.

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(2014). A Simple Model of Orientation Encoding Accounting For Multivariate Neural Noise. 6th Workshop of the Computational Neuroscience Network in Marseille.

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(2013). Active inference, eye movements and oculomotor delays. The 7th Japanese-French Frontiers of Science Symposium.

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(2012). Active inference, smooth pursuit and oculomotor delays. Proceedings of AREADNE, Santorini, Greece, 21-24 June 2012, published by The AREADNE Foundation, Inc., Cambridge, Massachusetts, USA, http://areadne.org.

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(2010). Probabilistic models of the low-level visual system: the role of prediction in detecting motion. LADISLAV TAUC & GDR MSPC NEUROSCIENCES CONFERENCE, From Mathematical Image Analysis to Neurogeometry of the Brain.

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(2009). Dynamics of cortical networks including long-range patchy connections. Eighth Göttingen Meeting of the German Neuroscience Society.

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(2008). Adaptive Sparse Spike Coding : applications of Neuroscience to the compression of natural images. Optical and Digital Image Processing Conference 7000 - Proceedings of SPIE Volume 7000, 7 - 11 April 2008.

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(2007). Topics in Dynamical Neural Networks: From Large Scale Neural Networks to Motor Control and Vision. Topics in Dynamical Neural Networks: From Large Scale Neural Networks to Motor Control and Vision.

(2007). Introduction. The European Physical Journal Special Topics.

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(2007). Dynamical Neural Networks: modeling low-level vision at short latencies. Topics in Dynamical Neural Networks: From Large Scale Neural Networks to Motor Control and Vision.

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(2007). Bayesian modeling of dynamic motion integration. Neuro-Computation: From Sensorimotor Integration to Computational Frameworks.

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(2007). PyNN: towards a universal neural simulator API in Python. *Sixteenth Annual Computational Neuroscience Meeting: CNS2007, Toronto, Canada. 7–12 July 2007.

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(2007). On efficient sparse spike coding schemes for learning natural scenes in the primary visual cortex. *Sixteenth Annual Computational Neuroscience Meeting: CNS2007, Toronto, Canada. 7–12 July 2007.

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(2007). Neural Codes for Adaptive Sparse Representations of Natural Images. Mathematical image processing meeting (Marseille, France) September 5, 2007.

(2006). Dynamical contrast gain control mechanisms in a layer 2/3 model of the primary visual cortex. The Functional Architecture of the Brain : from Dendrites to Networks. Symposium in honour of Dr Suzanne Tyc-Dumont. 4- 5 May 2006. GLM, Marseille, France.

(2006). Dynamical contrast gain control mechanisms in a layer 2/3 model of the primary visual cortex. Physiogenic and pathogenic oscillations: the beauty and the beast, 5th INMED/TINS CONFERENCE SEPTEMBER 9 - 12, 2006, La Ciotat, France.

(2006). Bayesian modeling of dynamic motion integration. 1ère conférence francophone NEUROsciences COMPutationnelles (NeuroComp).

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(2006). An efficiency razor for model selection and adaptation in the primary visual cortex. *Fifteenth Annual Computational Neuroscience Meeting (CNS2006).

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(2002). Visual Strategies for Sparse Spike Coding. Actes de Neurosciences et Sciences de l’Ingenieur, L’Agelonde,.

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