Wulfram Gerstner

photo placeholder image
Computational Neuroscience Laboratory

EPFL IC IINFCOM LCN1
AAB 1 35 (Bâtiment AAB)
Station 15
CH-1015 Lausanne

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

EPFL SV BMI LCN2
AAB 1 35 (Bâtiment AAB)
Station 19
CH-1015 Lausanne

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

EPFL SV SSV-GE
SG 1310.3 (Bâtiment SG)
Station 15
CH-1015 Lausanne

Web site:  Web site:  https://sv.epfl.ch/education

EPFL IC SIN-GE
INN 112 (Bâtiment INN)
Station 14
CH-1015 Lausanne

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

EPFL IC SSC-GE
INR 130 (Bâtiment INR)
Station 14
CH-1015 Lausanne

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

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

vCard
Administrative data

Fields of expertise

 Computational Neuroscience 

Publications

Selected publications

Teaching & PhD

Teaching

Computer Science

Physics
Life Sciences Engineering
Communication Systems

PhD Programs

Doctoral program in computer and communication sciences

Doctoral Program in Neuroscience

Doctoral Program Digital Humanities

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.