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Emmanuel Daucé

  • National Institute of Health and Medical Research
  • 5h-indexImpact measure calculated using publication and citation counts. Updated daily.
  • 84CitationsNumber of citations received by Emmanuel's publications. Updated daily.

About

Emmanuel Daucé is associate professor at the Ecole Centrale de Marseille, doing his research in Computational Neuroscience at the "Institut de Neurosciences des Systèmes" (France), a joint research unit (Inserm/ CNRS / Aix-Marseille Université). He graduated from the Ecole Nationale Supérieure d'Electronique, d'Electrotechnique, d'Informatique et d'Hydraulique de Toulouse (1995), and obtained a Ph.D in Knowledge Representation and Formal reasoning from the Ecole Nationale Supérieure de l'Aeronautique et de l'Espace (2000), under the supervision of Bernard Doyon (Inserm) and Manuel Samuelides (ISAE), on learning and plasticity in artificial neural networks with random recurrent connectivity graphs. He contributed extend the model to a multi-populations, and spatio-temporal sequence learning. Further developments include various neurally plausible reinforcement learning schemes in closed-loop control systems, the study of spike-timing dependent plasticity in balanced networks of spiking neurons and models of dynamic retention in discrete neural-fields. He also contributed develop on-line learning methods for non-stationary data streams (including Brain Computer Interfaces), and participated in modelling brain non-stationarities with simple neural-mass dynamics on large-scale connectivity graphs.

Co-authors (18)

Publications (5)

  • Optimizing P300-speller sequences by RIP-ping groups apart

    • Thomas E
    • Clerc M
    • Carpentier A
    • et al.
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  • A Model of Neuronal Specialization Using Hebbian Policy-Gradient with "Slow" Noise

    • Dauce E
    • Alippi C
    • Polycarpou M
    • et al.
    N/AReaders
    N/ACitations
  • Hebbian reinforcement learning in a modular dynamic network

    • Dauce E
    • Schaal S
    • Ijspeert A
    • et al.
    N/AReaders
    N/ACitations
  • Novelty Learning in a Discrete Time Chaotic Network

    N/AReaders
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  • Un processus d'apprentissage hebbien dans des réseaux dynamiques à temps discret

    N/AReaders
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Professional experience

INSERM