Lets look at some of its Hyperparameters
Autoencoder Specific
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Compression factor (Latent space size)
Loss function (mse?)
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Neural Network architecture
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Number of layers
Number of neurons in each layer (Shape of the matrices $A_n$)
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Optimisation parameters
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Learning Rate
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Controls how fast the parameters are found
To high value makes the training unstable
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Batch size
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Controls how many samples are averaged together.
Lower values make the training more stable, but also the result less optimal
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