GRAPH2SEQ: GRAPH TO SEQUENCE LEARNING WITH ATTENTION-BASED NEURAL NETWORKS Introduction 提出了一种新的基于注意力的图序列学习神经网络模型Graph2Seq。Graph2Seq模型遵循传统的编解码器方法,包含两个主要组件,一个图形编码器和一个序列解码器。本文提出的图形编码器旨在学习表达性节点嵌入,并
Jay will be teaching you about a particular RNN architecture called "sequence to sequence". In this case, you feed in a sequence of data and the network will output another sequence. This is typically used in problems such as machine translation, where you'd feed in a sentence in English ...
describes Google's architecture for machine translation, which uses skip connections between encoder and decoder layers. Next topic:Hyperparameters Previous topic:Sequence to Sequence (seq2seq) Need help? Try AWS re:Post Connect with an AWS IQ expert Did this page help you? Yes No Provide ...
Our network architecture features a special recurrent neural network cell for feature learning and extraction instead of convolutional layers and another type of cell for further processing. To evaluate the suitability of this inhomogenously stacked recurrent neural network, experiments on three different ...
论文github地址 值得阅读与一试: https://github.com/facebookresearch/fairseq 以往谈到sequence to sequence,往往会下意识地想到 RNN, 但这篇文章告诉我们,CNN 不仅可以做 sequence to sequence,不仅在大规模机器翻译的训练数据上结果比 RNN 要好,而且模型更加易于优...Attentive...
In these models, the Transformer, a new sequence-to-sequence attention-based model relying entirely on self-attention without using RNNs or convolutions, achieves a new single-model state-of-the-art BLEU on neural machine translation (NMT) tasks. Since the outstanding performance of the ...
Convolutional Sequence to Sequence Learning 贡献: introduce an architecture based entirely on convolutional neural networks. Multi-layer convolutional neural networks create hierarchical representations over the input sequence in which nearby input elements interact at lower layers while distant elements interact...
第三周 序列模型和注意力机制(Sequence models & Attention mechanism) 基础模型(Basic Models) 在这一周,你将会学习 seq2seq(sequence to sequence)模型,从机器翻译到语音识别,它们都能起到很大的作用,从最基本的模型
Signal forecasting with a Sequence-to-Sequence (seq2seq) Recurrent Neural Network (RNN) model in TensorFlow - Guillaume Chevalier - guillaume-chevalier/seq2seq-signal-prediction
补充一些自己的东西,把自己的思路理清。 主要是这几篇论文...2014年发表,作者Cho,Bahdanau,Bengio,是seq2seq的前身。提出一种RNN的Encoder-Decoder模型型,用于统计机器翻译SMT。但是模型只是作为SMT框架的一部分进行的 从Machine Translation 到Sequence to Sequence(Seq2seq)、Attention、Pointer Network(prt network)...