Lecturer: Marc-Oliver Gewaltig
Assistants: Berat Denizdurduran, Gianrocco Lazzari, He Xu, Michael Moret
Course - Lectures on Monday morning 10-12 (INF 1)
hand out of exercises on Monday
discussion of Exercises (Group 1): Wednesday 10-12 (INM 200)
discussion of Exercises (Group 2): Wednesday 13-15 (INR 219)
Neural networks are a fascinating interdisciplinary field where physicists, biologists, and computer scientists work together in order to better understand the information processing in biology. In this course paradigms of unsupervised learning and reinforcement learning are discussed from a biological point of view and analyzed mathematically.
Recommended text books:
Neural Networks: A Comprehensive Foundation (2nd ed) by S. Haykin.
- Theoretical Neuroscience by P. Dayan and L.F. Abbott.
Introduction to the Theory of Neural Computation by J. Herz, A. Krogh and R. G. Palmer.
Reinforcement Learning by R. Sutton and A. Barto.
Spiking Neuron Models by W. Gerstner and W. Kistler.
Neuronal Dynamics by W. Gerstner, W. M. Kistler, R. Naud and L. Paninski.