Lets look at some of its Hyperparameters
Autoencoder Specific
<l2st>
Compression factor (Latent space size)
Loss function (mse?)
</l2st>
Neural Network architecture
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Number of layers
Number of neurons in each layer (Shape of the matrices $A_n$)
</l2st>
Optimisation parameters
<l2st>
Learning Rate
<l3st>
Controls how fast the parameters are found
To high value makes the training unstable
</l3st>
Batch size
<l3st>
Controls how many samples are averaged together.
Lower values make the training more stable, but also the result less optimal
</l3st>
</l2st>
