序列到序列(Sequence-to-Sequence)模型 在这里,编码器和解码器的输入和输出特征数并不固定,而是取决于具体的任务和数据。例如,编码器可能接收一个包含10个词的句子,而解码器可能输出一个包含15个词的句子。 所以在sm的预测里,一般是sequence-to-sequence模型,输出维度取决于自己选。 自动编码器(Autoencoders)和序列
Deep stacked autoencoder sequence to sequence autoencoder bidirectional long short-term memory network wind speed forecasting solar irradiation forecasting 1. Introduction With the rapid development of smart grids, microgrids have been garnering increasing interest as a unique method of power delivery. A...
Besides, the stacked long short-term memory sequence-to-sequence autoencoder (SLSTM-SSAE) approach was exploited for malware classification and detection. Moreover, the arithmetic optimization algorithm (AOA) technique was exploited for the hyperparameter selection technique. The simulation outcomes of ...
此外Sequence To Sequence模型自然也可以运用到声音上——“Auto-encoder – Speech”。它可以给变长的语音序列降维,将一段声音讯号变成固定长度的向量。比如不同的描述dog的语音经过降维变成向量后,它们分布的距离是比较接近的[8]。 图13 自动编码器-语音 但是这种应用也有一点问题,就如图12种,因“never”和“ever...
Source code for the NAACL 2019 paper "SEQ^3: Differentiable Sequence-to-Sequence-to-Sequence Autoencoder for Unsupervised Abstractive Sentence Compression" - liangsi03/seq3
This model combines an LSTM-based deep stacked sequence-to-sequence autoencoder-based approach with the one-class SVM, creating a powerful framework for effective anomaly detection. By leveraging the strengths of both the LSTM-based deep stacked sequence-to-sequence autoencoder and one-class SVM,...
Source code for the NAACL 2019 paper "SEQ^3: Differentiable Sequence-to-Sequence-to-Sequence Autoencoder for Unsupervised Abstractive Sentence Compression" - cbaziotis/seq3
图像:最近的图像量化进展,如Vector Quantized Variational Autoencoder (VQ-VAE) (van den Oord et al., 2017) 和 Vector Quantized Generative Adversarial Networks (VQGAN) (Esser et al., 2021),提供了一种有效的处理方法。例如,一个分辨率为256×256的图像可以表示为一个较短的离散代码序列,如长度为16×16...
The encoder reads the source sentences X = [ x_{1}, ... , x_{T} ], and use a RNN to encode it as a seqence of the RNN's hidden state sequence H = [ h_{1}, ... , h_{T} ], in which h_{i} = [ \overleftarrow{ h } , \overrightarrow{ h } ] of the bi-direc...
First, an advanced landmark location pipeline is used to accurately locate the facial landmarks, which can effectively reduce landmark shake. Then, a part-based autoencoder is presented to encode face images into a low-dimensional space and obtain compact representations. A sequence-to-sequence ...