Deep Learning

Understanding RNN: Recurrent Neural Networks and Their Implementation in PyTorch

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Understanding RNN: Recurrent Neural Networks and Their Implementation in PyTorch

Click the “MLNLP” above to select the “Star” public account Heavyweight content delivered first-hand From | Zhihu Author | Lucas Address | https://zhuanlan.zhihu.com/p/85995376 Column | Deep Learning and Sentiment Analysis Editor | Machine Learning Algorithms and Natural Language Processing Understanding RNN: Recurrent Neural Networks and Their Implementation in PyTorch Recurrent Neural Networks (RNN) are a … Read more

Introduction to Recurrent Neural Networks (RNN): Vector to Sequence, Sequence to Sequence, Bidirectional RNN, Markovization

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Introduction to Recurrent Neural Networks (RNN): Vector to Sequence, Sequence to Sequence, Bidirectional RNN, Markovization

Author: David 9 Address: http://nooverfit.com/ RNN seems to be better at information preservation and updating, while CNN seems to excel at precise feature extraction; RNN has flexible input and output dimensions, while CNN dimensions are relatively rigid. 1Question When talking about Recurrent Neural Networks, our first reaction might be: time sequence. Indeed, RNNs are good … Read more

Combining CNNs and RNNs: Genius or Madness?

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Combining CNNs and RNNs: Genius or Madness?

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 However, the latest research trends in CNN may render this idea outdated.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

Understanding the Differences Between CNN, DNN, and RNN

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Understanding the Differences Between CNN, DNN, and RNN

Broadly speaking, NN (or the more elegant DNN) can indeed be considered to encompass specific variants like CNN and RNN. In practical applications, the so-called deep neural network DNN often integrates various known structures, including convolutional layers or LSTM units. However, based on the question posed, the DNN here should specifically refer to a fully … Read more

Latest RNN Techniques: Attention-Augmented RNN and Four Models

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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

A Beginner’s Guide to Using RNNs

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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

Introduction to RNN and ODE: Understanding RNNs

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Introduction to RNN and ODE: Understanding RNNs

Author: Su Jianlin Affiliation: Guangzhou Flame Information Technology Co., Ltd. Research Direction: NLP, Neural Networks Personal Homepage: kexue.fm I had originally decided to stop working with RNNs as they actually correspond to numerical methods for ODEs (Ordinary Differential Equations). This realization provided me with insights into something I have always wanted to do—using deep learning … Read more

Understanding Recurrent Neural Networks (RNNs)

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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

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

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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

Progress in Neural Network Renormalization Group

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Progress in Neural Network Renormalization Group

Renormalization group is a fundamental concept in physics research. It is not only a powerful tool for studying phase transitions and critical phenomena, as well as strong coupling problems, but it also shapes physicists’ worldview: physics is an effective theory about the emergence of phenomena at different scales and energy levels. In the practical applications … Read more