通过实验,我们可以得出以下的结论,所有的模型都使用固定数量的参数,在一些数据集上,,GRU比LSTM单元在CPU时间上的收敛速度上更快,并且在参数更新和泛化上性能更佳。 2.Recurrent Neural Network RNN是一个卷积前馈(conventional feedforward)神经网络的一个拓展,它可以处理可变长度的输入序列(variable-length sequence inp...
论文笔记:Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling,程序员大本营,技术文章内容聚合第一站。
《A review of irregular time series data handling with gated recurrentneural networks》 这篇的主要贡献,一个是对时序数据插补的技术做了一个比较好的总结,一个是对天然不规则数据上的处理方法做了比较好的总结,最后就是大量魔改的循环神经网络模型的总结。虽然很多都没看过也不懂,但是我大受震撼。 什么是时序...
Machine Learning —— Recurrent Neural Network Machine Learning —— Recurrent Neural Network RNN,或者说最常用的LSTM,一般用于记住之前的状态,以供后续神经网络的判断,它由input gate、forget gate、output gate和cell memory组成,每个LSTM本质上就是一个neuron,特殊之处在于有4个输入: z z z和三门控制信号 ...
1. 论文相关 Published as a conference paper at ICLR 2016 2. 摘要 图结构数据经常出现在化学、自然语言语义、社会网络和知识库等领域。在这项工作中,我们研究了图形结构输入的特征学习技术。我们的出发点是之前在图神经网络方面的工作(Scarselli等人,2009),我们将其修改为使用门控循环单元(gated recurrent units)...
Recent architectural developments have enabled recurrent neural networks (RNNs) to reach and even surpass the performance of Transformers on certain sequence modeling tasks. These modern RNNs feature a prominent design pattern: linear recurrent layers interconnected by feedforward paths with multiplicative ...
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 th...
The paper evaluates three variants of the Gated Recurrent Unit (GRU) in recurrent neural networks (RNNs) by retaining the structure and systematically reducing parameters in the update and reset gates. We evaluate the three variant GRU models on MNIST and IMDB datasets and show that these GRU-...
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 th...
A new model based on gate recurrent unit (GRU) neural network and attention mechanism is constructed in our study. A bidirectional GRU network was designed to extract key features from forward and backward well logs data along depth direction, and attention mechanism was introduced to assign ...