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Optimal Transport for Machine Learning - Gabriel Peyre, Ecole Normale Superieure
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- 1 Intro
- 2 Probability Distributions in Data Sciences
- 3 1. Optimal Transport
- 4 Kantorovitch's Formulation
- 5 Optimal Transport Distances
- 6 Entropic Regularization
- 7 Sinkhorn Divergences
- 8 Sample Complexity
- 9 Density Fitting and Generative Models
- 10 Deep Discriminative vs Generative Models
- 11 Training Architecture
- 12 Automatic Differentiation
- 13 Examples of Images Generation
- 14 Generative Adversarial Networks
- 15 Open Problems
