How does binary cross entropy loss work on autoencoders?

In the context of autoencoders the input and output of the model is the same. So, if the input values are in the range [0,1] then it is acceptable to use sigmoid as the activation function of last layer. Otherwise, you need to use an appropriate activation function for the last layer (e.g. linear which … Read more

Deep Belief Networks vs Convolutional Neural Networks

Generally speaking, DBNs are generative neural networks that stack Restricted Boltzmann Machines (RBMs) . You can think of RBMs as being generative autoencoders; if you want a deep belief net you should be stacking RBMs and not plain autoencoders as Hinton and his student Yeh proved that stacking RBMs results in sigmoid belief nets. Convolutional … Read more

What is the purpose of the add_loss function in Keras?

I’ll try to answer the original question of why model.add_loss() is being used instead of specifying a custom loss function to model.compile(loss=…). All loss functions in Keras always take two parameters y_true and y_pred. Have a look at the definition of the various standard loss functions available in Keras, they all have these two parameters. … Read more

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