Bi-RNN

Nested LSTM: A Novel LSTM Extension for Long-Term Information Processing

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Nested LSTM: A Novel LSTM Extension for Long-Term Information Processing

Selected from arXiv Author:Vihar Kurama Translated by Machine Heart Contributors: Liu Xiaokun, Li Yazhou Recently, CMU and the University of Montreal proposed a novel multi-level memory RNN architecture—Nested LSTM. When accessing internal memory, Nested LSTM has greater flexibility compared to traditional Stacked LSTM, allowing it to handle longer temporal scales of internal memory; experiments also … Read more

A Beginner’s Guide to Implementing LSTM

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A Beginner's Guide to Implementing LSTM

【Introduction】Time series modeling is widely used in machine translation, speech recognition, and other related fields, making it an essential technology in the AI domain. This article will teach you how to build a Long Short-Term Memory network (LSTM) from scratch, using Bitcoin price prediction as an example. Author | Brian Mwangi Translated by | Zhuanzhi … Read more

Essential Guide to LSTM: From Basics to Functionality Explained

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Essential Guide to LSTM: From Basics to Functionality Explained

Selected from echen Translated by Machine Heart Contributors: Machine Heart Editorial Team Long Short-Term Memory (LSTM) is a crucial neural network technology that has been widely applied in many fields, including speech recognition and natural language processing. In this article, Edwin Chen provides a systematic introduction to LSTM. Machine Heart has translated this article. The … Read more

Why LSTM is So Effective?

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Why LSTM is So Effective?

Follow the public account “ML_NLP“ Set as “Starred“, heavy content delivered first-hand! From | Zhihu Author | Tian Yu Su https://www.zhihu.com/question/278825804/answer/402634502 Editor | Deep Learning This Small Matter Public Account This article is for academic exchange only. If there is any infringement, please contact the background for deletion. I have done some similar work, let … Read more