## Course summary

• Type MOOC course
• Period Always open
• Learning Time Study freely
• Course approval method Automatic approval
• Certificate Issue Online
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### Instructor Introduction

• KAIST 산업및시스템공학과 문일철 교수님

KAIST 산업및시스템공학과 부교수
KAIST 김재철AI대학원 겸임교수
KAIST 항공우주공학과 겸임교수
KAIST 안보융합연구원 겸임교수
한국인공지능학회 교육이사

### Lecture plan

★강의목록
1. CHAPTER 1 : Basic of GAN
1. Basic of GAN: Implicit Distribution
1. Basic of GAN: Overview and Notations
1. Basic of GAN: Formalization
1. Basic of GAN: Analogy
1. Basic of GAN: Quiz 1
2. CHAPTER 2 : GAN Objectives and Structures
1. GAN Objectives and Structures: Loss Function
1. GAN Objectives and Structures: Jensen-Shannon Divergence
1. GAN Objectives and Structures: Training
1. GAN Objectives and Structures: Theoretical Results
1. GAN Objectives and Structures: Quiz 2
3. CHAPTER 3 : Mode Collapse of GAN
1. Mode Collapse of GAN: Introduction
1. Mode Collapse of GAN: Unrolled GAN(1)
1. Mode Collapse of GAN: Unrolled GAN(2)
1. Mode Collapse of GAN: Effects of Mode Collapsing by Unrolled GAN
1. Mode Collapse of GAN: Quiz 3
4. CHAPTER 4 : Latent and Conditional Modeling on GAN
1. Latent and Conditional Modeling on GAN: cGAN
1. Latent and Conditional Modeling on GAN: Adding Latent Variable to GAN
1. Latent and Conditional Modeling on GAN: InfoGAN(1)
1. Latent and Conditional Modeling on GAN: InfoGAN(2)
1. Latent and Conditional Modeling on GAN: cGAN vs InfoGAN
1. Latent and Conditional Modeling on GAN: Quiz 4
5. CHAPTER 5 : f-GAN
1. f-GAN: Generalize Divergence
1. f-GAN: Convex Conjugate Function
1. f-GAN: f-divergence
1. f GAN: Optimal Tau of Fenchel Conjugate
1. f-GAN: Variational Divergence Minimization(1)
1. f-GAN: Variational Divergence Minimization(2)
1. f-GAN: Difference of Two Probability Distributions
1. f-GAN : Quiz 5
6. CHAPTER 6 : GAN with IPM
1. GAN with IPM: Definitions and Types
1. GAN with IPM: GAN+MMD(1)
1. GAN with IPM: GAN+MMD(2)
1. GAN with IPM: Parallel Line Density Example
1. GAN with IPM: Wasserstein Distance
1. GAN with IPM: Kantorovich-Rubinstein Duality
1. GAN with IPM: Wasserstein as Primal LP
1. GAN with IPM: Wasserstein as Dual LP
1. GAN with IPM: Property of Dual LP on Wasserstein Distance
1. GAN with IPM: Lipschitz Continuity
1. GAN with IPM: Dual Problem of Wasserstein Distance
1. GAN with IPM: Kantorovich-Rubinstein Duality and Wassertein GAN
1. GAN with IPM: Quiz 6
7. ★강의 수강 후 의견을 부탁드리겠습니다.★
1. 교수님 강의에 대한 별점을 매겨주세요. 여러분의 의견이 많은 도움이 됩니다:D