Covers the fundamentals of graph theory, including vertices, edges, degrees, walks, connected graphs, cycles, and trees, with a focus on the number of edges in a tree.
Distinguishes between subgraphs and induced subgraphs in graph theory, illustrating the construction of minimal spanning trees.
Covers the concept of the exponential family and discusses forward and backward maps, expensive computations, parameters, functions, and convexity.
Explores causal inference, directed graphs, and fairness in algorithms, emphasizing conditional independence and the implications of DAGs.
Explores Belief Propagation in graphical models, factor graphs, spin glass examples, Boltzmann distributions, and graph coloring properties.
