6.268 Network Science and Models


Class Info

Introduces the main mathematical models used to describe large networks and dynamical processes that evolve on networks. Static models of random graphs, preferential attachment, and other graph evolution models. Epidemic propagation, opinion dynamics, social learning, and inference in networks. Applications drawn from social, economic, natural, and infrastructure networks, as well as networked decision systems such as sensor networks.

This class has 6.041B, and 18.06 as prerequisites.

6.268 will be offered this semester (Spring 2019). It is instructed by P. Jaillet and J. N. Tsitsiklis.

This class counts for a total of 12 credits. This is a graduate-level class.

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MIT 6.268 Network Science and Models Related Textbooks

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