Wulfram Gerstner

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Computational Neuroscience Laboratory

Web site:  Web site:  https://sph.epfl.ch/

Web site:  Web site:  https://sin.epfl.ch

Web site:  Web site:  https://ssc.epfl.ch

EPFL Comité Campus Genève
Campus Biotech B1
Chemin des Mines 9
CH-1202 Genève

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Administrative data

Fields of expertise

 Computational Neuroscience, Theoretical Neuroscience

Publications

Selected publications

Teaching & PhD

Teaching

Computer Science

Physics
Life Sciences Engineering
Communication Systems

Courses

State of the Art Topics in Neuroscience XIII

(Coursebook not yet approved by the section)

Artificial neural networks/reinforcement learning

Since 2010 approaches in deep learning have revolutionized fields as diverse as computer vision, machine learning, or artificial intelligence. This course gives a systematic introduction into influential models of deep artificial neural networks, with a focus on Reinforcement Learning.

Computational neurosciences : neuronal dynamics

In this course we study mathematical models of neurons and neuronal networks in the context of biology and establish links to models of cognition. The focus is on brain dynamics approximated by determinstic or stochatic differnetial equations.