Explore the Graph Convolutional Network (GCN) paper in this 27-minute video explanation. Dive into the abstract, problem introduction, and inner workings of GCNs. Learn about the theoretical derivation of GCNs, followed by a practical node classification example. Conclude with a discussion on the paper's results and final thoughts. Gain insights into this important graph-based machine learning technique, suitable for those interested in advanced deep learning concepts and graph neural networks.
Overview
Syllabus
- Introduction
- Sponsored Segment: Link
- Abstract and overview
- Introduction to the problem
- How GCNs work
- Theory of GCN derivation
- GCN Node classification example
- Conclusions & Results
- Ending thoughts
Taught by
Aladdin Persson
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