- A Representing the input financial data in a lower-dimensional latent space
- B Reconstructing the original data space
- C Maximizing the Kullback-Leibler divergence and the reconstruction loss
- D Creating fresh samples through the reconstruction process
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Answer:
A
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The encoder in the VAE (Variational Autoencoder) training process is responsible for:
Representing the input financial data in a lower-dimensional latent space
The encoder takes the input data and maps it to a lower-dimensional latent space, where the data is represented as a mean and variance, enabling efficient data compression and dimensionality reduction.
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