When
This hybrid workshop provides graduate students with the necessary skills for understanding and applying graph machine learning techniques. Among the covered topics are the fundamentals of graph theory, practical applications of graph neural networks, and advanced methods for graph-based data analysis.
We meet in the Weaver Science and Engineering Library in Rm 212. You can also join us via Zoom at https://arizona.zoom.us/j/86423223879.
Data/Topic/YouTube Link
04/01/24: Part 1: Why Graph ML and basics of graph theory
04/08/24: Part 2: Node representations: Deepwalk and node2vec
04/15/24: Part 3: Basics of GNN - node classification
04/22/24: Part 4: Introduction to Graph Convolutions
04/29/24: Part 5: Introduction to Graph Attention Network
Note: GitHub repositories and registration links will be available closer to the start date.