2022年9月24日 · 为了准确和及时预测局部区域的降雨及温度，提出了一种基于 Attention 和 LSTM 组合模型 ( ALSTM) 的 关联多值 预测算法。 该算法利用天气时间序列中 的前期数据，对下一 …

跑完原生的ALSTM Benchmark发现不考虑交易成本的净值曲线居然近似相当于基准的沪深300指数（即几乎无超额收益），而考虑了交易成本的超额收益居然是负的，观察前面模型训练的每 …

1.预测模型：ALSTM-Attentive LSTM. 先看整体结构： 和标准的lstm相比，在上面的倒数第二层增加了“ temporal attention layer ”，也就是说，在预测前，综合使用了所有时刻隐藏层，并给它 …

In this paper, we propose ALSTM model, which is based on the Long Short Term Memory (LSTM) recurrent neural network and the attention mechanism for multi-scenario bandwidth prediction. …

其实本文模型的原型是ALSTM (Attentive LSTM), 是机器学习选股常见的，也是微软qlib自带的一个baseline，只不过本文作者为了降低模型的过拟合并提高泛化能力，在每一次Iteration里面增 …

2020年7月25日 · In this paper, we produce a novel framework (ALSTM) based on the Attention mechanism and Long Short-Term Memory (LSTM), which associates structure learning with …

To run the proposed Adv-ALSTM, ALSTM, and LSTM on the ACL18 and KDD17 dataset, run the commands in the hyperparameter file.

This paper proposes a novel attention-based long short-term memory (ALSTM) method for improved design of GC models to diagnose the alarm root-cause and identify the alarm …

PyTorch implementation of the adaptive LSTM (https://arxiv.org/abs/1805.08574), an extension of the standard LSTM that increases model flexibility through adaptive parameterization. The …

The project is all about reproducing a working version of Adversarial Attention Based LSTM for TensorFlow 2. This new version is available in AdvALSTM.py with the object AdvLSTM. More …