Wulfram Gerstner

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Laboratory of Computational Neuroscience

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

Web site: Web site: https://lcn1.epfl.ch/index.html

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Administrative data

Fields of expertise

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

Biological modeling of neural networks

In this course we study mathematical models of neurons and neuronal networks in the context of biology and establish links to models of cognition.

State of the Art Topics in Neuroscience XII

Surprise, Reward, and Curiosity are drives of human, animal, and robot behavior. The class links theories of reinforcement learning with human behavior beyond standard notions of reward.

Artificial neural networks

  • Simple perceptrons for classification
  • Reinforcement Learning 1: Bellman equation and SARSA
  • Reinforcement Learning 2: variants of SARSA, Q-learning, n-step-TD learning
  • Reinforcement Learning 3: Policy gradient
  • Deep Networks 1: BackProp and Multilayer Perceptrons
  • Deep