… Long Short-Term Attention (LSTA), a new recurrent neural unit that augments LSTM with
built-in spatial attention … • We present Long Short-Term Attention (LSTA), a new recurrent unit …

… the attention mechanism into the inner cell of LSTM. More than processing long short term
dependencies, LSTA can focus on important information of the sequences with the attention …

… the long term dependencies of the traffic flow evolution. To address this issue, we propose
to … an attention mechanism to the long short-term memory network for short-term traffic flow …

… long short-term memory (Bi-LSTM)-based network is designed for HSI classification.
Moreover, a spatial–spectral attention … Moreover, the proposed spatial–spectral attention …

… Our model utilizes neural attention mechanism with Bidirectional Long Short-Term Memory
… The contribution of this paper is using BLSTM with attention mechanism, which can automat…

… based on LSTM and attention mechanism for short-term photovoltaic power forecasting. …
data and learn long-term dependency information in sequence. We applied the trained attention …

… long-term memory currently in a state of heightened activation or (2) the focus of attention or
… with the focus of attention depicted as a subset of the activated portion of long-term memory. …

The stock market is known for its extreme complexity and volatility, and people are always
looking for an accurate and effective way to guide stock trading. Long short-term memory (…

… Short-term load forecasting (STLF) plays an important … short-term load forecasting method
based on attention mechanism (AM), rolling update (RU) and bi-directional long short-term …

… Meanwhile, attention visualization makes models interpretation providing … attention-weight
matrix is generated independently by the spatial attention module and the temporal attention …