Computer scienceData scienceMachine learningGenerative modeling

Variational autoencoders

The reparametrization trick

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In VAEs, how does the reparametrization trick affect stochastic backpropagation during training?

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It introduces more randomness into the learning process, leading to a non-deterministic training outcome

It allows the backpropagation to bypass the stochastic node

It alters the structure of the neural network, allowing backpropagation to impact all layers directly

It avoids treating stochastic variables as constant during optimization

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