Detailed Course Information |
Fall 2025 Semester
Jan 18, 2026 |
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| NETS 7332 - Machine Learning with Graphs |
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Covers a number of advanced topics in machine learning and data mining on graphs, including vertex classification, graph clustering, link prediction and analysis, graph distance functions, graph embedding and representation learning, deep learning for graphs, anomaly detection, graph summarization, network inference, adversarial learning on networks, and notions of fairness in social networks. Seeks to familiarize students with state-of-the-art descriptive and predictive algorithms on graphs. Requires a foundational understanding of calculus and linear algebra, probability, machine learning or data mining, algorithms, and programming skills.
4.000 Credit hours 4.000 Lecture hours Levels: Graduate Schedule Types: Lecture Interdisc Studies - Soc Sc/Hum Department Course Attributes: GS Col Socl Sci & Humanities, Crosslisted Course Restrictions: Must be enrolled in one of the following Programs: PhD Network Science Must be enrolled in one of the following Levels: Graduate Must be enrolled in one of the following Classifications: Graduate Prerequisites: Graduate level PHYS 5116 Minimum Grade of C |
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