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Ho et al.의 DDPM 논문을 심층 분석한다. Forward/Reverse diffusion process, 변분 하한(ELBO), 노이즈 스케줄링, 단순화된 학습 목표(simplified objective)를 수식으로 유도하고, DDIM, Latent Diffusion, Stable Diffusion으로의 진화까지 총정리한다.
Generative-model
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Ian Goodfellow의 GAN 원본 논문부터 DCGAN, WGAN, Progressive GAN, StyleGAN까지 — 생성적 적대 신경망의 핵심 이론인 minimax 게임, Nash 균형, 학습 불안정성 해결법을 수식과 함께 분석하고, GAN 계보의 진화를 총정리한다.