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Centre de recherche

Scientific Conference - Eilif Muller

Bridging scales of learning from cortical biophysics to deep neural networks

Friday 22 May 2020 from 09:00 at 10:00


  • Eilif Muller, PhD
    • Researcher in AI

Zoom conference
Password: 942740

The fields of neuroscience and artificial intelligence have a long history of fertile bi-directional interactions. On the one hand, important inspiration for the development of artificial intelligence systems has come from the study of natural systems of intelligence, the mammalian neocortex in particular. On the other, important inspiration for models and theories of the brain have emerged from artificial intelligence research. A central question at the intersection of these two disciplines is concerned with the processes by which sensory perception is learned in the neocortex. In the field of deep learning, neocortical learning inspires active areas of research aiming at matching its data efficient incremental learning and out-of-distribution generalization, but largely ignoring decades of neuroscientific insights or constraints. I will present recent advances in our understanding of the synaptic, dendritic and circuit physiology of the neocortex made possible in part by simulation-based approaches, which provide inspiration to solve these key open challenges in deep learning, but also suggest a radically new perspective on the processes of learning in the neocortex. 

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Updated on 5/20/2020
Created on 5/20/2020
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