Explore the world of Graph Machine Learning in this comprehensive video walkthrough of a blog post. Dive into research tips, learn how to get started with Graph ML, and discover fascinating applications in various fields. Gain insights on graph embedding methods, Graph Neural Networks, and their parallels with CNNs. Explore topics such as GNN expressivity, dynamic graphs, and unsupervised graph learning. Get acquainted with datasets, benchmarks, and related research subfields. Perfect for those looking to understand the potential of Graph ML and its applications in fake news detection, fundamental science, and even antibiotic discovery.
Overview
Syllabus
Research/learning challenges
What is Graph ML? We're all graphs
Cool Graph ML applications
Fake news and fundamental science
Halicin a potent antibiotic discovered by a GNN
Contrasting Graph ML with CV and NLP
Resources - graph embedding methods
Graph Neural Networks
Top to bottom approach - high level resources
Spatial methods
Simple baselines sometimes work great!
Parallel with CNNs
GNN expressivity
Dynamic graphs
Unsupervised graph learning and geometric DL
Datasets/benchmarks and newsletter
GAT project
Related research subfields
Taught by
Aleksa Gordić - The AI Epiphany
