Lectures related to Algorithmic Paradigms for Dynamic Graph Problems

Covers classical models of epidemic spreading and dynamics on networks with examples.

Explores statistical analysis of network data, covering graph structures, models, statistics, and sampling methods.

Explores Belief Propagation in graphical models, factor graphs, spin glass examples, Boltzmann distributions, and graph coloring properties.