Networks

Link Prediction Given network-structured data, predict whether a link exists between two nodes. General types of prediction tasks on graphs: graph-level (e.g. will a molecule bind to a receptor implicated in a disease?), node-level (e.g. what is the identity of each node?), and edge-level (e.g. does this edge exist; what value does it have?). Applications include: predicting drug-drug interactions (common in treating patients with complex/co-existing diseases) as they may cause changes in the drugs' pharmacological activity ....

Examples of Influential Power; Modeling Influence with Graphs; The Contagion Model; Infection Models: SI, SIS, SIR; Bayesian Rating; Networks: Friends, Money and Bytes [COS 381];