Bidirectional recurrent neural network(BRNN) is a noncausal generalization of recurrent neural network(RNN). It can not learn remote information efficiently due to the problem of ...
: Recurrent neural networks possess interesting universal approximation capabilities, making them good candidates for time series modeling. Unfortunately, long term dependencies ar...
Learning long-term temporal dependencies with recurrent neural networks can be a difficult problem. It has recently been shown that a class of recurrent neural networks called NA...
Abstract. Reservoir computing approaches have been successfully applied to a variety of tasks. An inherent problem of these approaches, is, however, their variation in performance ...
Knowing the number of residue contacts in a protein is crucial for deriving constraints useful in modeling protein folding, protein structure, and/or scoring remote homology searc...