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I’m Japanese. I also speak English a little.
To my knowledge, a common basic assumption under the probabilistic modeling of the data or the relationship between the data is to deal with the input X and the output Y. Most of the probabilistic models esp. machine learning models only consider these two variables.
Regression models treat the maps from X to Y. In the sense of probabilistic modeling, it is about P(Y|X). In this setting, X is seen as the “user-defined” deterministic variable. On the other hand, generative modeling treat both X and Y probabilistically, say P(Y,X). With P(Y,X), we can “generate” data (X,Y) by sampling from it.
横だが、コンピュータサイエンス分野でもUNIX哲学で「すべてのプログラムはフィルター」というけど、AI界隈は「生成」という語を使うのでまあいいやってなってるので確かにそこでツ...
生成モデルの「生成」は入力の確率分布もモデリングするという意味であって、「フィルター」というのは入力はモデリングせず入力を出力に変換する部分のことを言っていて、これは...
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日本語分かんのか、外人かお前はよ 余計な能書き垂れねぇでいいからよ
I’m Japanese. I also speak English a little. To my knowledge, a common basic assumption under the probabilistic modeling of the data or the relationship between the data is to deal with the input X and the output Y. Most of the probabilistic models ...
That's not what I'm talking about, blah, blah, blah. First of all, I don't like your arrogant attitude that you are smarter than me. First of all, you should realize that you are just an idiot. The fool who is unaware is the most troublesome. I am not...
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