Selected from Medium Author: Piotr Tempczyk Translated by Machine Heart Contributors: Chen Yunzhu, Liu Xiaokun There are many studies on visualization in the field of convolutional neural networks, but there are not enough similar tools for LSTM. Visualizing LSTM networks can yield interesting results; due to their time-related characteristics, we can explore the relationships between … Read more
Selected from GitHub Author: Tigran Galstyan et al. Translated by Machine Heart Contributors: Nurhachu Null, Jiang Siyuan For humans, transliteration is a relatively easy and interpretable task, making it suitable for explaining what neural networks do and whether their actions are similar to those of humans on the same task. Therefore, we start with the … Read more
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
Click the card below to follow the “CVer” WeChat public account AI/CV heavy content delivered instantly Click to join —> the CV WeChat technical exchange group Reprinted from: New Intelligence | Edited by: Xinpeng Hao Kun [Guide] Recently, Jürgen Schmidhuber, the father of LSTM, reviewed the history of artificial intelligence since the 17th century. In … Read more
Follow the public account “ML_NLP“ Set as “Starred“, delivering heavy content to you first! Source | Zhihu Address | https://www.zhihu.com/question/62399257/answer/241969722 Author | Scofield Editor | Machine Learning Algorithms and Natural Language Processing Public Account This article is for academic sharing only. If there is an infringement, please contact us to delete the article. To put … Read more
【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
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
Editorial Department WeChat Official Account Keywords All Network Search Latest Ranking “Quantitative Investment”: Rank One “Quantization”: Rank One “Machine Learning”: Rank Four We will continue to strive To become a high-qualityFinancial and Technical public account Introduction to LSTM Networks LSTM Networks are a type of Recurrent Neural Network (RNN) first introduced by Sepp Hochreiter and … Read more
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
Previously, I introduced Recurrent Neural Networks (RNNs), which are fascinating because they can effectively utilize historical information. For instance, using the previous video frame to infer the current video content. In earlier articles, we also discussed that traditional RNNs cannot learn connections that are too far apart in time. Sometimes, we only need the previous … Read more