Bptt trains all weights, while rc only output weights

When using backpropagation through time with RNNs, all weights are learned. In contrast, in reservoir computing, only the output weights which read off the harvested dynamics are learned through a closed-form linear regression. In a sense, reservoir computing explodes the input in a high-dimensional space which is then linearly separable.

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