The Wasserstein Metric a.k.a Earth Mover's Distance: A Quick and Convenient Introduction 

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I totally agree...this is math, we need some silence to focus and understand

"A bit" annoying. Because apparently there is some possible world where atonal fretless bass is only "a bit" annoying.

That's the infamous Tony Levin on bass.

It's the amazing Tony Levin.

Not a bit, VERY annoying

Thank you so much. It works ;)

Thanks, that is much better

x2 speed is better

oh s^it it works

but with that speed the background music is not harmonic as before😢

Thanks for asking a good question.

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Thanks for watching.

But i like this slow style. Everyone has different preferences

The BGM is from Tony Levin.

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Chart Denkra thanks for watching

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Yes there are.

Thanks for watching. Yes, the video is not a complete explanation, more like just the beginning. For more, you'll have to do some more research. Have a look at some of the video comments and description.

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Don’t rely on this video for the exact details of the computation. You can check out the paper references in the description.

Take a look at the first few pages of "Optimal transport meets graph spectra" by Shiping Liu. It is one of the many good introductions that will clarify your questions. In a simplified manner, the answers to your questions are: The moved quantities are infinitesimal in nature. They correspond to densities. The destination in the target of a source point is what one tries to obtain by solving the Monge version of the problem. In the Kantorovich version, a source point can be split and assigned to multiple target points. These transportation maps (for Monge) and transportation plans (for Kantorovich) are obtained by solving optimization problems. Existence of the solution is easier for the Kantorovich problem. The total sizes of the source and target are assumed to be normalized to one, in general. Optimal transport is a rigorous way to get the distance between distributions.

Nice share. Thx pal

hi the link is not available now

@@harikannantube nice explanation. I tried to read the text but this isn't available now. Could you sent to me, please?

@Alexander Yau, @Samuel Francisco, the article title and author are mentioned now.

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Yes, you need a good controller to watch these videos. Probably I should have read the papers I refer to more carefully before making the video.

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Durand Sinclair Thanks for watching.

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Hi Tejas. It's a fine question. I didn't explain the mathematics very well in the video. I would need to make a follow up video to present the mathematics better. In the meantime, you can have a look at the references made in the comments.

@@BobLaramee Thanks for the quick reply and for nice explanation in video ^^. It really helps students like us.

thanks for watching.

Thanks for watching.

True. i had no idea how much demand there is for this material. A follow-up is on my todo list.

Is there anyway I can contact you( maybe email)? I was planning on doing a research paper walkthrough(kinda like my first but not exactly) of WASSERSTEIN AUTO-ENCODERS: openreview.net/pdf?id=HkL7n1-0b This paper was named one of the top 5 papers for deep learning in 2018. My goal with these videos is to get more more familiar with research papers.

Sure. A skype call is also fine. My email is r.s.laramee at swansea.ac.uk. My skype name is rlaramee.

Awesome I will definitely contact you

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I think the result will depend on the implementation. Thanks for watching

The music is from Tony Levin's World Diary album. Not a very popular one but I really like it.

Where are you studying?

It was just an experiment. My other videos have no background music.

There are some pointers in the comments.

@@BobLaramee thanks, but can i just simply say wasserestein distance as the disimilarity cost one has to pay for any deviation?

Big cup for big mouth 😉

Aneeshaa Chowdhry yes

It is by Tony Levin on an obscure album called world diary

I agree it's not perfect

High standards.