Machine Learning on Real World Networks
Explore networks in natural and socio-technological systems. Examine network structure and dynamics, machine learning on real networks, clustering; network models, small worlds, scale free networks, preferential attachment, community structure, network-on-chip optimization and control, epidemics and rumors, human mobility, network embedding, deep learning on graphs, graph neural networks, and other networks. Electrical and Computer Engineering 381K (Topic 20) and Electrical Engineering 381K (Topic 20) may not both be counted.
Prerequisites & course information
Explore networks in natural and socio-technological systems. Examine network structure and dynamics, machine learning on real networks, clustering; network models, small worlds, scale free networks, preferential attachment, community structure, network-on-chip optimization and control, epidemics and rumors, human mobility, network embedding, deep learning on graphs, graph neural networks, and other networks. Electrical and Computer Engineering 381K (Topic 20) and Electrical Engineering 381K (Topic 20) may not both be counted.
Sources
- Course catalogue ↗2026-2027