An interpretable LSTM neural network for autoregressive exogenous model

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Guo, Tian; Lin, Tao; Lu, Yao;
  • Subject: Statistics - Machine Learning | Computer Science - Learning

In this paper, we propose an interpretable LSTM recurrent neural network, i.e., multi-variable LSTM for time series with exogenous variables. Currently, widely used attention mechanism in recurrent neural networks mostly focuses on the temporal aspect of data and falls ... View more
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