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1 February 2021: One event

  • Invited Talks

    Monday 1 February 14:00-15:30 - Remy Kusters - Physics Inspired Machine Learning Lab, CRI, Paris

    Deep learning driven model discovery for physics

    Résumé : With the growing need for interpretability of machine learning-based predictions in quantitative science our team develops DeepMoD: An open source Deep learning based framework for Model Discovery. Model discovery aims at finding interpretive models in the form of partial differential equations from large spatio-temporal data-sets. By integrating advances in symbolic and statistical machine learning DeepMoD seeks an interpretable model from noisy and oftentimes very sparse data-sets. We illustrate this approach on several problems in the context of (bio)physics, mechanics and fluid dynamics, such as the Burgers’, Korteweg-de Vries, advection-diffusion and Keller-Segel equations.
    contact: S. Rafai

    Lieu : online

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