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Classroom Contents
The Devil is in the GAN - Defending Deep Generative Models Against Adversarial Attacks
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- 1 Introduction
- 2 Research Goals
- 3 What are Deep Generative Models
- 4 Applications of Deep Generative Models
- 5 What Could Go Wrong
- 6 What Makes a Successful Attack
- 7 Model Inspection
- 8 Brute Force Sampling
- 9 mnist
- 10 Training
- 11 Can you do something better
- 12 Approach trail
- 13 Approach schematic
- 14 Student Model
- 15 Redundancy
- 16 Token Example
- 17 Stylegun
- 18 Attack Goals
- 19 Basic Defenses
- 20 Whitebox Access
