Latest RNN Techniques: Attention-Augmented RNN and Four Models

Latest RNN Techniques: Attention-Augmented RNN and Four Models

1 New Intelligence Compilation Source: distill.pub/2016/augmented-rnns Authors: Chris Olah & Shan Carter, Google Brain Translator: Wen Fei Today is September 10, 2016 Countdown to AI WORLD 2016 World Artificial Intelligence Conference: 38 days Countdown for Early Bird Tickets: 9 days [New Intelligence Guide] The Google Brain team, led by Chris Olah & Shan Carter, has … Read more

Overview of Dropout Application in RNNs

Overview of Dropout Application in RNNs

[Introduction] This article provides the background and overview of Dropout, as well as a parameter analysis of its application in language modeling using LSTM/GRU recurrent neural networks. Author|Adrian G Compiled by|Zhuanzhi Organized by|Yingying Dropout Inspired by the role of gender in evolution, Hinton et al. first proposed Dropout, which temporarily removes units from the neural … Read more

Solving the Vanishing Gradient Problem in RNNs

Solving the Vanishing Gradient Problem in RNNs

Click the above “MLNLP” to select the “star” public account Essential content delivered promptly Author: Yulin Ling CS224N(1.29)Vanishing Gradients, Fancy RNNs Vanishing Gradient The figure below is a more vivid example. Suppose we need to predict the next word after the sentence “The writer of the books”. Due to the vanishing gradient, the influence of … Read more

Attention Models: The Future Beyond RNN and LSTM

Attention Models: The Future Beyond RNN and LSTM

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

A Beginner’s Guide to Using RNNs

A Beginner's Guide to Using RNNs

Excerpt from Medium Author: Camron Godbout Translated by: Machine Heart Contributors: Duxiade What are Recurrent Neural Networks (RNNs) and how do we use them? This article discusses the basics of RNNs, which are increasingly popular deep learning models. The intention of this article is not to delve into the obscure mathematical principles but to provide … Read more

Enhancing RNN with Adaptive Computation Time for Multi-Factor Stock Selection

Enhancing RNN with Adaptive Computation Time for Multi-Factor Stock Selection

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

Understanding Recurrent Neural Networks (RNNs)

Understanding Recurrent Neural Networks (RNNs)

↑↑↑ Follow “Star Mark” Datawhale Daily Insights & Monthly Study Groups, Don’t Miss Out Datawhale Insights Focus: Neural Networks, Source: Artificial Intelligence and Algorithm Learning Neural networks are the carriers of deep learning, and among neural network models, the most classic non-RNN model belongs here. Although it is not perfect, it possesses the ability to … Read more

Using Neural Networks to Continue Writing Game of Thrones

Using Neural Networks to Continue Writing Game of Thrones

Author: Sam Hill Translators: Tian Ao, Song Qingbo, Aileen, Long Muxue Reply “novel” in the background to download the complete new novel created by the neural network~ Winter is coming…… Season 7 of “Game of Thrones” has ended, but it is said that the last six episodes of this series will not air until spring … Read more

The Father of Recurrent Neural Networks: Building Unsupervised General Neural Network AI

The Father of Recurrent Neural Networks: Building Unsupervised General Neural Network AI

Recommended by New Intelligence Source: Authorized Reprint from InfoQ Translator: He Wuyu [New Intelligence Overview] Jürgen Schmidhuber, the scientific affairs director at the Swiss AI lab IDSIA, led a team in 1997 to propose the Long Short-Term Memory Recurrent Neural Network (LSTM RNN), which simplifies time-dependent recurrent neural networks, thus earning him the title of … Read more

The Rise and Fall of Neural Networks in the 1990s

The Rise and Fall of Neural Networks in the 1990s

Excerpt from andreykurenkov Author: Andrey Kurenkov Translated by Machine Heart Contributors: salmoner, Electronic Sheep, Sister Niu Niu, Ben, Slightly Chubby This is part three of the History of Neural Networks and Deep Learning (see Part One, Part Two). In this section, we will continue to explore the rapid development of research in the 1990s and … Read more