Author | Bill Vorhies Translator | Gai Lei Editor | Vincent AI Frontline Overview: From some interesting use cases, it seems we can completely combine CNN and RNN/LSTM. Many researchers are currently working on this research. However, the latest research trends in CNN may render this idea outdated. For more quality content, please follow the … Read more
Big Data Digest Works Compiled by: Wan Jun, Da Jie Qiong, Qian Tian Pei Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM) networks, which have been incredibly popular, it’s time to abandon them! LSTM and RNN were invented in the 1980s and 1990s, resurrected in 2014. In the following years, they became the go-to … Read more
0. Introduction After reading many blog posts and tutorials about RNN online, I felt they were all the same, providing a vague understanding but failing to explain it clearly. RNN is the foundation of many complex models, and even in transformers, you can see the influence of RNN, so it is essential to have a … Read more
Editorial Department WeChat Official Account KeywordsSearch across the webLatest Ranking 『Quantitative Investment』: Ranked First 『Quantitative』: Ranked First 『Machine Learning』: Ranked Third We will continue to work hard To become a qualityfinancial and technical public account across the web Today we will read an article from Guosen Securities Research Introduction to RNN The biggest feature that … Read more
Canonical transformations are classical methods used by physicists, mechanical engineers, and astronomers to handle Hamiltonian systems. By finding suitable variable substitutions, canonical transformations can simplify, or even completely solve the dynamics of Hamiltonian systems. For instance, in the 19th century, French scientist Charles Delaunay published approximately 1800 pages of analytical derivations attempting to simplify the … Read more
5.4 The Intellectual The Intellectual Image Source: Freepik ● ● ● Written by｜Zhang Tianrong As physicist and Manhattan Project leader Oppenheimer said, “We are not just scientists; we are also human.” Where there are humans, there is a community, and the scientific world is no exception. People often say that “science knows no borders, but … Read more
Machine Heart reported Machine Heart Editorial Department Can neural networks complete various tasks without learning weights? Are the image features learned by CNN just what we think they are? Are neural networks merely combinations of functions with no other meaning? From this paper, the answers to these questions seem to be affirmative. Yesterday, a paper … Read more
Report by New Intelligence Source: aiweirdness, gizmodo Translated by: Xiao Qin [New Intelligence Overview]One of the specialties of neural networks is image recognition. Tech giants like Google, Microsoft, IBM, and Facebook all have their own photo tagging algorithms. However, even the top image recognition algorithms can make very strange mistakes, they only see what they … Read more
Authorized Reprint from CSDN Source: codewords.recurse.com Translator: Liu Diwei, Reviewer: Liu Xiangyu, Editor: Zhong Ha Website: http://www.csdn.net Abstract: This article is based on the author’s reading of papers and practical tests, attempting to deceive neural networks. It gradually analyzes neural networks and the mathematical principles behind them, from tool installation to model training. The article … Read more
Big Data Digest works, reposting requires authorization Author| Han Xiaoyang && Long Xincheng Thanks| Owen for translating and providing part of the content from Recurrent Neural Networks Tutorial part 1 Source|http://blog.csdn.net/han_xiaoyang/article/details/51253274 Big Data Digest’s “Machine Learning” column is established! We welcome everyone to leave valuable comments and submit articles to us. How to join us? … Read more