gaussian
US /'gaʊsɪrn/
・UK /'gaʊsɪən/
A1 初級
adj.形容詞高斯
影片字幕
"天堂或遺忘 "官方預告片 ("Paradise or Oblivion" official trailer)
02:57
- There will come a time called the gaussian curve
被稱為高斯曲線的那種時刻將會到來
熱烈交流：女性體育運動中的變性女性 (HEATED Exchange: Trans Women in Women's Sports)
39:45
- That's the one with the thing the net Which is very different from male lacrosse So I just think that it comes down to the biological makeup of like the training used for it and everything But I agree with a lot of the stuff that they say I'm not like They shouldn't do it, but I just think it should be so you think and I just want to make sure I get your argument You think that they shouldn't do it because it confers an unfair advantage on the person even if they've met their hormone requirements because as a biological male ages before they transition they have certain intrinsic advantages a Height for example, maybe in basketball or now that doesn't mean all men are tall but on a Gaussian curve It means that more men are tall than women So is that I don't want to mischaracterize.
但我同意他們說的很多話，我並不是說他們不應該這樣做，我只是認為應該這樣做，你是這麼想的，我只是想確保我理解了你的論點，你認為他們不應該這樣做，因為這給了他們不公平的優勢，即使他們已經達到了荷爾蒙要求、你認為他們不應該這麼做，是因為這樣做會給人帶來不公平的優勢，即使他們已經達到了荷爾蒙要求，因為生理上的男性在變性之前就已經老了，他們有一些內在的優勢，比如說身高，也許在籃球或者現在，這並不意味著所有的男性都很高，但在高斯曲線上，這意味著更多的男性比女性高。
Inverse matrices, column space and null space | 3blue1brown 線性代數精髓第7章（Inverse matrices, column space and null space | Essence of linear algebra, chapter 7）
12:09
- Keywords: "Gaussian elimination" and "Row echelon form."
我想在我實際加在這裏的大部分的價值是在直覺方面的。
但人工智能影像和視頻究竟是如何工作的？| 韋爾奇實驗室特邀視頻 (But how do AI images and videos actually work? | Guest video by Welch Labs)
37:20
- One way to arrive at this result is to show that given the noise we add in our forward process is Gaussian, for sufficiently small step sizes our reverse process will also follow a Gaussian distribution, where our model actually learns the mean of this distribution.
得出這一結果的方法之一是證明，如果我們在正向過程中添加的噪聲是高斯分佈，那麼在步長足夠小的情況下，我們的反向過程也將遵循高斯分佈，而我們的模型實際上學習的是這一分佈的均值。
- Since our model just predicts the mean of our normal distribution, to actually sample from this distribution, we need to add zero mean Gaussian noise to our model's predicted value, which is precisely what the DDPM image generation process does when we add random noise after each step.
由於我們的模型只是預測正態分佈的平均值，要真正從該分佈中採樣，我們需要在模型預測值中添加零平均高斯噪聲，而這正是 DDPM 影像生成過程中我們在每一步後添加隨機噪聲時所要做的。
