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Related lectures (29)

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Anomalies and Non-exchangeable: Statistical Analysis of Network Data

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

Networked Control Systems: Stability and Dropout Analysis

Explores the stability of Networked Control Systems under deterministic packet drops and the estimation of the maximal drop rate.

Statistical Analysis of Network Data

Introduces network data structures, models, and analysis techniques, emphasizing permutation invariance and Erdős-Rényi networks.

Inference for Stochastic Processes: Large Networks Analysis

Explores inference for stochastic processes, emphasizing large networks analysis and the need for new theories and methods.

Block Models: Continued Analysis

Explores the stochastic blockmodel, spectral clustering, and non-parametric understanding of blockmodels, emphasizing metrics for comparing graph models.

Distances and Motif Counts

Explores distances on graphs, cut norms, spanning trees, blockmodels, metrics, norms, and ERGMs in network data analysis.

Graph Statistics: Random Graphs, Graph Homomorphisms, and Network Analysis

Explores graph statistics, random graph generation, network analysis, centrality measures, and clustering coefficients.

Statistical Analysis of Network Data

Explores epidemics in network data, covering SIR model, basic reproductive ratio, percolation, directed networks, and maximum likelihood estimation.

Biclustering & latent variables: statistical analysis of network data

Explores biclustering techniques and latent variables in network data analysis.