Computer Science 691NR - S-NeuralNetworks&Neurodynamics

This course covers various aspect of neural networks, from fundamentals to advanced concepts. Topics include feed-forward neural networks, kernel-based approaches, deep learning, recurrent neural networks, Hopfield networks, Kohonen Self-Organized Maps, Grossberg Adaptive Resonance Theory, Helmholtz machines, MDL, Symbolic neural nets, and space-time neurodynamics, with links to computational neuroscience. Theoretical foundations of supervised, unsupervised, and reinforcement learning are described.

Open to Graduate Computer Science students only. MEETS WITH COMPSCI 591NR. UNDERGRADUATE COURSE IN ALGORITHMS EQUIVALENT TO COMPSCI 311 IS ASSUMED. STUDENTS NEEDING INSTRUCTOR PERMISSION MUST REQUEST OVERRIDES VIA THE ON-LINE FORM: https://www.cics.umass.edu/overrides.