Computer Science 591NR - 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. This course counts as a CS Elective toward the CS major (BA or BS).

Undergraduates must have completed CMPSCI 311 with a grade of 'C' or better. LECT 01 FOR UNDERGRADS; LECT 02 FOR GRADS. MEETS WITH COMPSCI 691NR. STUDENTS NEEDING INSTRUCTOR PERMISSION MUST REQUEST OVERRIDES VIA THE ON-LINE FORM: https://www.cics.umass.edu/overrides.