【参文】 时间，网络

一、时间序列

1. Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling

abstract
In this paper we compare different types of recurrent units in recurrent neural networks (RNNs). Especially, we focus on more sophisticated units that implement a gating mechanism, such as a long short-term memory (LSTM) unit and a recently proposed gated recurrent unit (GRU). We evaluate these recurrent units on the tasks of polyphonic music modeling and speech signal modeling. Our experiments revealed that these advanced recurrent units are indeed better than more traditional recurrent units such as tanh units. Also, we found GRU to be comparable to LSTM.
摘要：
本文比较了递归神经网络（RNN）中不同类型的递归单元。特别是，我们关注实现门控机制的更复杂的单元，例如长短期记忆（LSTM）单元和最近提出的门控循环单元（GRU）。我们在复调音乐建模和语音信号建模任务中评估这些重复单元。我们的实验表明，