Graph SAGE - Inductive Representation Learning on Large Graphs - GNN Paper Explained

Graph SAGE - Inductive Representation Learning on Large Graphs - GNN Paper Explained

Aleksa Gordić - The AI Epiphany via YouTube Direct link

Intro

1 of 13

1 of 13

Intro

Class Central Classrooms beta

YouTube playlists curated by Class Central.

Classroom Contents

Graph SAGE - Inductive Representation Learning on Large Graphs - GNN Paper Explained

Automatically move to the next video in the Classroom when playback concludes

  1. 1 Intro
  2. 2 Problems with previous methods
  3. 3 High-level overview of the method
  4. 4 Some notes on the related work
  5. 5 Pseudo-code explanation
  6. 6 How do we train Graph SAGE?
  7. 7 Note on the neighborhood function
  8. 8 Aggregator functions
  9. 9 Results
  10. 10 Expressiveness of Graph SAGE
  11. 11 Mini-batch version
  12. 12 Problems with graph embedding methods drift
  13. 13 Comparison with GCN and GAT

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Someone learning on their laptop while sitting on the floor.