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A recursive network is only a recurrent network generalization. In a recurrent network, weights are exchanged (and dimensionality stays constant) over the sequence and, in a test cycle, you can see a list of varying lengths then you will find in train times while working with position-dependent weights. For the same reason, the weights are distributed in a recursive network (and dimensionality stays constant).

Recursive Neural Networks (RvNNs)

In order to understand Recurrent Neural Networks (RNN), it is first necessary to understand the working principle of a feedforward network. In short, we can say that it is a structure that produces output by applying some mathematical operations to the information coming to the neurons on the layers.

The information received in the Feedforward working structure is only processed forward. In this structure, an output value is obtained by passing the input data through the network. …

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Ensar Seker

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