Generating new data with VAEs
hamish - 29/05/2020
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- bit like the "identity function" of NNs
- aim is to learn the input via a small "bottleneck"
- break this task up into an "encoder" and "decoder"
Autowhat now?
(Autoencoder)
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encoder
decoder
"bottleneck"
Latent Space
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???
Can we force the latent space to be more consistent?
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Add noise before bottleneck
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- forces VAE to compensate for noise
- does this by learning to place similar things close to one another
- different things far apart
- more consistent space
How does this work?
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"8 direction"
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most 8s are over here
"Shift" in a direction
- find direction of feature we like
- use encoder to find position of image in latent space
- move in feature direction
- decode from that point
Downside: Implementing this is surprisingly hard, even with the code
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Sunglasses
Black hair
Female
So why do we care?
- We (CIA) want to be able to provide actions so people can lower their energy use
- Would like to be able to "simulate" scenarios like if user got an EV
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Shift in "EV direction"
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learnt people charge their EVs overnight
- not really learnt the peaks you get with EVs
- causes issues with standby
- lose strong signal from other devices
David Ha https://worldmodels.github.io/
Generating new data with VAEs
By Hamish dickson
Generating new data with VAEs
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