Lectures in course MATH-448: Statistical analysis of network data

Explores link prediction, logistic regression, causal inference, and biclustering in statistical network analysis.

Introduces hypergraphs, generalizing graphs by allowing subsets of nodes to form edges and exploring their applications in various fields.

Explores biclustering techniques and latent variables in network data analysis.

Explores anomaly detection in network data and exchangeability extensions for statistical analysis.

Explores link prediction in networks, covering missing edges, probabilistic methods, and causal inference challenges.

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