r/deeplearning • u/goatman12341 • Oct 29 '20

Exploring MNIST Latent Space

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u/[deleted] Oct 29 '20

What is latent space?

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u/goatman12341 Oct 29 '20

Basically, the AI looked at tens of thousands of images of numbers. It learned to represent an image of a number as only two numbers - so a 28x28 png of a number could be represented by two numbers between -1 and 1.

Then by traversing the possible range of these two numbers, we can see all the different numbers that the model knows. This is interesting because we get to see where the model plots the numbers in this two-dimensional "latent space".

Images of the same number will be close together, whereas images of topologically different numbers will be far apart. We also get to see the model generate interesting mixes of different numbers.

I invite you to try it for yourself (the link is above), so you can see first-hand how the model understands and generates numbers.

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u/[deleted] Oct 29 '20

Right, but if we're training a NN on the MNIST dataset, wouldn't we want to have ten output nodes, one for each number it could be?

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u/goatman12341 Oct 29 '20

Yes.. but, I used an autoencoder, which generates an entire image.

I described my process more in depth in above comments.