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인공지능 및 기계학습 심화3
KAIST 산업및시스템공학과 문일철 교수님
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인공지능 및 기계학습 심화3
인공지능 및 기계학습 심화3
http://kooc.kaist.ac.kr/aiml-adv3/lecture/1290856
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CHAPTER 1 : Basic of GAN
Basic of GAN: Implicit Distribution
Basic of GAN: Overview and Notations
Basic of GAN: Formalization
Basic of GAN: Analogy
Basic of GAN: Quiz 1
CHAPTER 2 : GAN Objectives and Structures
GAN Objectives and Structures: Loss Function
GAN Objectives and Structures: Jensen-Shannon Divergence
GAN Objectives and Structures: Training
GAN Objectives and Structures: Theoretical Results
GAN Objectives and Structures: Quiz 2
CHAPTER 3 : Mode Collapse of GAN
Mode Collapse of GAN: Introduction
Mode Collapse of GAN: Unrolled GAN(1)
Mode Collapse of GAN: Unrolled GAN(2)
Mode Collapse of GAN: Effects of Mode Collapsing by Unrolled GAN
Mode Collapse of GAN: Quiz 3
CHAPTER 4 : Latent and Conditional Modeling on GAN
Latent and Conditional Modeling on GAN: cGAN
Latent and Conditional Modeling on GAN: Adding Latent Variable to GAN
Latent and Conditional Modeling on GAN: InfoGAN(1)
Latent and Conditional Modeling on GAN: InfoGAN(2)
Latent and Conditional Modeling on GAN: cGAN vs InfoGAN
Latent and Conditional Modeling on GAN: Quiz 4
CHAPTER 5 : f-GAN
f-GAN: Generalize Divergence
f-GAN: Convex Conjugate Function
f-GAN: f-divergence
f GAN: Optimal Tau of Fenchel Conjugate
f-GAN: Variational Divergence Minimization(1)
f-GAN: Variational Divergence Minimization(2)
f-GAN: Difference of Two Probability Distributions
f-GAN : Quiz 5
CHAPTER 6 : GAN with IPM
GAN with IPM: Definitions and Types
GAN with IPM: GAN+MMD(1)
GAN with IPM: GAN+MMD(2)
GAN with IPM: Parallel Line Density Example
GAN with IPM: Wasserstein Distance
GAN with IPM: Kantorovich-Rubinstein Duality
GAN with IPM: Wasserstein as Primal LP
GAN with IPM: Wasserstein as Dual LP
GAN with IPM: Property of Dual LP on Wasserstein Distance
GAN with IPM: Lipschitz Continuity
GAN with IPM: Dual Problem of Wasserstein Distance
GAN with IPM: Kantorovich-Rubinstein Duality and Wassertein GAN
GAN with IPM: Quiz 6
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교수님 강의에 대한 별점을 매겨주세요. 여러분의 의견이 많은 도움이 됩니다:D
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f GAN: Optimal Tau of Fenchel Conjugate
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f GAN: Optimal Tau of Fenchel Conjugate - 이현민
f GAN: Optimal Tau of Fenchel Conjugate - 이현민
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f-GAN: f-divergence
f-GAN: Variational Divergence Minimization(1)
