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Temporal Graph Networks - GNN Paper Explained

Aleksa Gordić - The AI Epiphany via YouTube

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Overview

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This course provides a visual deep dive into Temporal Graph Networks for dynamic graphs. It explains temporal sampling, information leakage, memory and message aggregation, temporal graph attention, time representations, and interaction prediction.

Syllabus

Dynamic graphs
Suboptimal strategies
Terminology, temporal neighborhood
High-level overview of the system
We need to go deeper
Using temporal information to sample
Information leakage and the solution
Main modules explained
Memory staleness problem
Temporal graph attention
Vector representation of time
Batch size tradeoff
Results and ablation studies
Recap of the system
Some confusing parts

Taught by

Aleksa Gordić - The AI Epiphany

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