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    Friday, December 1st. 2017 – Konrad Koerding

    thumbnail of 2017 Koerding-3Neuroscience Seminar Series:
    Friday, December  1st, 2017 , 11:30 am, Salle des conférences (3rd Floor), Centre Universitaire des Saints-Pères, 45 rue des Saints-Pères, 75006 Paris

    Konrad Koerding

    Professor – Department of Bioengineering and Department of Neuroscience

    University of Pennsylvania




    Rethinking the role of machine learning in neuroscience”



    The goal of much of computational biology is to numerically describe data from a system, but also to find ways of fixing it and to understand a system’s objectives, algorithms, and mechanisms. Here we will argue that, regardless the objective, machine learning should be a central contribution to progress in every flavor of biomedical science. Machine learning can typically better describe the data. In doing so it can also provide a benchmark for any other way of describing the data. Using examples from neuroscience we discuss how better performance matters for decoding models and how having a benchmark affects encoding models. Similar issues matter in medicine. As biomedical science evolves, machine learning is morphing into a critical tool across the full spectrum of scientific questions. 



    Eef Joosten: pointer1313@gmail.com

    Cecile Issard: cecile.issard@etu.parisdescartes.fr