gan (2) 썸네일형 리스트형 [Week7] Conditional generative model [Day3] 1. Conditional generative model Translating an image given "condition" We can explicitly generate an image corresponding to a given "condition"! sketch of a bag이 주어졌을 때 X인 이미지가 일어날 확률 1.1 Generative model vs. Conditional generative model Generative model은 랜덤 샘플을 생성 Conditional generative model은 조건이 주어졌을 때 랜덤 샘플을 생성 Example of conditional generative model - audio super resolution P (high resoluti.. [Week2] DL Basic - Generative Models [Day5] *Learning a Generative Model Suppose we are given images of dogs We want to learn a probability distribution p(x) such that Generation : 개와 같은 비슷한 이미지를 생성할 수 있음 Density estimation(anomaly detection) : p(x)의 x가 강아지 같은지 아닌지 분류 Unsupervised representation learning : feature learning Then, how can we represent p(x)? *Basic Discrete Distributions Bernoulli distribution : (biased) coin flip D = {Heads.. 이전 1 다음
