Timeline for How can neural networks be used to generate rather than classify?
Current License: CC BY-SA 4.0
8 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Oct 22, 2019 at 14:48 | vote | accept | CommunityBot | ||
| Oct 19, 2019 at 1:42 | history | edited | mshlis | CC BY-SA 4.0 |
edited body
|
| Oct 18, 2019 at 17:36 | comment | added | Neil Slater | @AbhasKumarSinha: It means that if you have some imagined target distribution over your data $\Omega$ that you want to generate but don't have a random function for it, then you can create that random function by mapping from the normal distribution in $z$. The function $f()$, if well trained, and fed with samples from the normal distribution as inputs, will create samples over your output space - which is what you want, a random generator for your target data. | |
| Oct 18, 2019 at 15:00 | comment | added | user27450 | What is the meaning of $f(z) $~ $\omega$? | |
| Oct 18, 2019 at 14:59 | comment | added | user27450 | hehe... I think I'm too much addicted to doing AI using C++ , Python... I've recently made an AI that generates Music using Long Term/Short Term Memory manipulation using AI, wanted to add some lyrics but I needed a better voice, so, I'm now learning to generate voice using AI. | |
| Oct 18, 2019 at 14:38 | comment | added | mshlis | Look into basic probability and I think your golden for the understanding. If you want something to get your hands dirty, just google "GAN GitHub" and you'll find tons of repos for starting point of generative models. Add more specifics to your search if your looking for something more specific. Being in high school shouldn't stop you-- Its actually great you're getting into this so early! | |
| Oct 18, 2019 at 14:18 | comment | added | user27450 | I think I really need to pass high school doing mathematics before reaching the discussion to the level of mathematics you are talking... | |
| Oct 18, 2019 at 14:00 | history | answered | mshlis | CC BY-SA 4.0 |