Provisional Schedule

• Tuesday 29th April, Lecture 1: Real-world networks: their structure, dynamics and statistics.
  Introduction to Erdös-Rényi graphs.

• Wednesday 30th April, Lecture 2: Analysis of Erdös-Rényi graphs (e.g. degree distribution,
  triangles, diameter) using the probabilistic method. Introduction to phase
  transitions

• Thursday 1st May, Lecture 3: Giant Component and Connectivity of Erdös-Rényi graphs.
  Branching process approximations and coupling. Stein-Chen method for
  Poisson approximations.

• Friday 2nd May, Lecture 4: Configuration model of random graphs. Distances and percolation
  ins such graphs.

• Tuesday 6th May, Lecture 5: Models of real-world networks (small-worlds and preferential
  attachment), Yule branching process and martingale methods.

• Wednesday 7th May, Lecture 6: Clustering in networks, Stochastic block model, clustering
  algorithms (modularity and spectral clustering)

• Thursday 8th May, Lecture 7: Dynamics on Networks (random walks and their algorithmic
  implications, epidemic models, computation and information diffusion) and
  spectral graph theory

• Friday 9th May, Lecture 8: Network control, models of viral marketing and competition in
  networks.