On Scrambling Phenomena for Randomly Initialized Recurrent Networks

Neural Information Processing Systems 

Recurrent Neural Networks (RNNs) frequently exhibit complicated dynamics, and their sensitivity to the initialization process often renders them notoriously hard to train.

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