What is the translation of " LSTMS " in English?

• LSTMS
• LSTM

Examples of using Lstms in Chinese and their translations into English

谢天谢地，LSTMs没有这个问题！!
Thankfully, LSTMs don't have this problem!

LSTMs中的重复模块含有4层.
The repeating module in an LSTM contains four interacting layers.

幸运的是，LSTMs并没有这个问题！!
Thankfully, LSTMs don't have this problem!

LSTMs是明确设计避免长期依赖问题的。
LSTMs are explicitly designed to avoid the long-term dependency problem.

但并非所有的LSTMs都与上述相同。
But not all LSTMs are the same as the above.

多尺度分层LSTMs是基于相同的思想构建的。
Multi-Scale Hierarchical LSTMs are built on the same idea.

LSTMs是明确设计避免长期依赖问题的。
LSTMs are specifically designed to avoid the problem of long-term dependencies.

写下一堆有关LSTMs的方程，这让LSTMs看起来很吓人。
Written down as a set of equations, LSTMs look pretty intimidating.

LSTMs就是被设计用来避免长期依赖问题的。
LSTMs are specifically designed to avoid the problem of long-term dependencies.

本文目前为止探讨了两种深度学习算法：CNNs和LSTMs。
This article has explored two deep learning algorithms so far: CNNs and LSTMs.

LSTMs还具有这种链状结构，但重复模块具有不同的结构。
LSTM also have such a chain structure, but the repeating module has a different structure.

这清楚地显示了LSTMs在分析时间序列和顺序数据方面的强大功能。
This clearly shows how powerful LSTMs are for analyzing time series and sequential data.

LSTMs还具有这种链状结构，但重复模块具有不同的结构。
LSTMs also have this chain like structure, but the repeating module has a different structure.

RNN（如果有紧密连接和非线性，现在f通常是LSTMs和GRUs的）。
RNN(If here is a densely connected unit and a nonlinearity, nowadays f is generally LSTMs or GRUs).

LSTMs同样会有这样的类链式结构，但其中重复模块具有不同的结构。
LSTM also have such a chain structure, but the repeating module has a different structure.

RNN(如果存在密集连接单元和非线性，现在f通常是LSTMS或Grus)。
RNN(If here is a densely connected unit and a nonlinearity, nowadays f is generally LSTMs or GRUs).

LSTMs也有这样一个链式结构，但是那个重复模块的结构是不一样的。
LSTM also have such a chain structure, but the repeating module has a different structure.

(2015)测试了超过10000种RNN架构，发现其中一些在某些具体任务上的表现优于LSTMs。
(2015) tested more than ten thousand RNN architectures, finding some that worked better than LSTMs on certain tasks.

LSTMs也有这样一个链式结构，但是那个重复模块的结构是不一样的。
LSTMs also have this chain like structure, but the repeating module has a different structure.

像Siri，Alexa，Cortana这样的对话媒介基本上致力于通过LSTMS和RNN简化语音识别技术。
Conversational agents like Siri, Alexa, Cortana basically work on simplifying the speech recognition techniques through LSTMs and RNNs.

LSTMs在序列预测问题中非常强大，因为它们能够存储过去的信息。
LSTMs are very powerful in sequence prediction problems because they're able to store past information.

LSTMs能够从时间序列数据中捕捉最重要的特征并进行关联建模。
LSTMs are capable of capturing the most important features from time series data and modeling its dependencies.

LSTMs可以给单元状态移除或者增加信息，由一个称为门（gate）的结构来控制。
The LSTM can remove or add information to the cell state, carefully regulated by structures called gates.

LSTMs已经被证明能够学习复杂的序列，比如像莎士比亚一样进行写作或创作原始的音乐。
LSTMs have been shown to be able to learn complex sequences, such as writing like Shakespeare or composing primitive music.

LSTMs在刚开始学习时比较复杂，但如果你感兴趣想要多了解一下，这篇文章讲解的非常清楚。
LSTMs can be quite confusing in the beginning but if you're interested in learning more this post has an excellent explanation.

LSTMs的固有特性使其成为涉及时间序列、非线性数据流的异常检测任务的理想选择。
The inherent properties of LSTMs makes them an ideal candidate for anomaly detection tasks involving time-series, non-linear numeric streams of data.

CNNLSTMs开发用来可视化序列预测问题和从图像序列生成文本描述的应用（例如：视频）。
CNN LSTMs were developed for visual time series prediction problems and the application of generating textual descriptions from sequences of images(e.g. videos).