Gunnar Carlsson - Deep Learning and TDA

Gunnar Carlsson - Deep Learning and TDA

Applied Algebraic Topology Network via YouTube Direct link

Feature Space Modeling

17 of 26

17 of 26

Feature Space Modeling

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Gunnar Carlsson - Deep Learning and TDA

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  1. 1 Intro
  2. 2 What is Deep Learning?
  3. 3 Problems
  4. 4 Convolutional Neural Networks
  5. 5 What Do We Want to know?
  6. 6 Mumford Data Set (De Silva, Ishkhanov, Zomorodian, C.)
  7. 7 Image Patch Analysis: Primary Circle
  8. 8 Image Patch Analysis: Three Circle Model
  9. 9 Image Patch Analysis: Klein Bottle
  10. 10 Primary Visual Cortex
  11. 11 Visual Pathway
  12. 12 How to Build Networks - Mapper Construction
  13. 13 Topological Analysis of Weight Spaces (MNIST)
  14. 14 Topological Analysis of Weight Spaces (VGG16)
  15. 15 Hard Code Primary Circle and Klein Bottle
  16. 16 Discovered Geometry
  17. 17 Feature Space Modeling
  18. 18 Microarray Analysis of Breast Cancer Cohort
  19. 19 Explaining the Different Cohorts
  20. 20 UCSD Microbiome
  21. 21 Generalized Convolutional Nets
  22. 22 Klein Bottle Connections
  23. 23 Generalization
  24. 24 Learning on Video
  25. 25 Gary Marcus
  26. 26 Applied Algebraic Topology Research Network

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