Class schedule - Spring 2026
| Date | Description | Slides | HW/Project | |
| Wed. 01/21 | Introductions, class organization, networks, context, examples | Block 1 | ||
| Fri. 01/23 | Graphs, digraphs, degrees, movement, strong and weak connectivity | Block 2a | ||
| Mon. 01/26 | Families, algebraic graph theory, data structures and algorithms | |||
| Wed. 01/28 | Inference, models, point and set estimates, hypothesis testing | Block 2b | ||
| Mon. 02/02 | Tutorials on inference about a mean and linear regression | |||
| Wed. 02/04 | Graph visualization, stages of network mapping, mapping Science | Block 3a | ||
| Fri. 02/06 | Large graph visualization, k-core decomposition, Internet mapping | |||
| Mon. 02/09 | Degree distributions, Erdos-Renyi random graphs and power laws | Block 3b | HW1 due | |
| Wed. 02/11 | Visualizing and fitting power laws, preferential attachment | |||
| Mon. 02/16 | Closeness, betweeness and eigenvector centrality measures | Block 3c | ||
| Wed. 02/18 | Web search, hubs and authorities, Markov chains review | |||
| Mon. 02/23 | PageRank, fluid and graph random walk models, distributed algorithms | |||
| Wed. 02/25 | Cohesive subgroups, clustering, connectivity, assortativity mixing | Block 3d | ||
| Fri. 02/27 | Strength of weak ties, community structure in networks | Block 4a | ||
| Mon. 03/02 | Girvan-Newmann method, hierarchical clustering, modularity | |||
| Wed. 03/04 | Modularity optimization, graph cuts, spectral graph partitioning | Proposal | ||
| Mon. 03/09 | Spring Break - No class | |||
| Wed. 03/11 | Spring Break - No class | |||
| Mon. 03/16 | Sampling, Horvitz-Thompson estimation, graph sampling designs | Block 4b | ||
| Wed. 03/18 | Network estimation of totals, groups size, degree distributions | |||
| Mon. 03/23 | Random graph models, model-based estimation, significance, motifs | Block 4c | HW2 due | |
| Wed. 03/25 | Small-world, preferential attachment and copying models | |||
| Mon. 03/30 | Latent network models, communities, random dot product graphs | Prog. Report | ||
| Wed. 04/01 | Topology inference, link prediction, scoring and classification | Block 4d | ||
| Mon. 04/06 | Traveling to IEEE ISBI'26 - No class | |||
| Wed. 04/08 | Traveling to IEEE ISBI'26 - No class | |||
| Mon. 04/13 | Inference of association networks, tomographic inference | HW3 due | ||
| Wed. 04/15 | Nearest-neighbor prediction of processes, Markov random fields | Block 5a | ||
| Mon. 04/20 | Graph kernel-regression, kernel design, protein function prediction | |||
| Wed. 04/22 | Diseases and the networks that transmit them, epidemic modeling | Block 5b | ||
| Mon. 04/27 | Machine learning on graphs, graph convolutional filters | Block 6a | HW4 due | |
| Wed. 04/29 | Graph neural networks, architectures, properties | |||
| Fri. 05/01 | In-class student project presentations | Presentation | ||