GRU

Deep Dive | Basics of Neural Networks: Seven Types of Units and Four Connection Methods

by
Deep Dive | Basics of Neural Networks: Seven Types of Units and Four Connection Methods

Excerpt from THE ASIMOV INSTITUTE Author: FJODOR VAN VEEN Translation by Machine Heart Contributors: Huang Xiaotian, Li Yazhou In September 2016, Fjodor Van Veen wrote an article titled “The Neural Network Zoo” (see the illustrated overview of neural network architectures: from basic principles to derivatives), which comprehensively reviewed a multitude of frameworks for neural networks … Read more

Understanding LSTM for Everyone

by
Understanding LSTM for Everyone

Recommended Reading Time: 8min~13min Reason for Recommendation: This is a summary and reflection after watching Professor Li Hongyi’s deep learning videos from National Taiwan University. After finishing the introduction of the first part, particularly the introduction to RNN and especially LSTM, I felt enlightened. 1 0. Starting with RNN Recurrent Neural Network (RNN) is a … Read more

GhostRNN: Cost-Effective Transformer Layer for RNN Model Optimization

by
GhostRNN: Cost-Effective Transformer Layer for RNN Model Optimization

Editor: Jizhi Shutong Recurrent Neural Networks (RNNs) based on long-range dependency modeling are widely used in various speech tasks, such as Keyword Spotting (KWS) and Speech Enhancement (SE). However, due to the power and memory limitations of low-resource devices, efficient RNN models are needed for practical applications. In this paper, the author proposes an efficient … Read more

Process Production Quality Prediction Algorithm Based on Mar-G LSTM

by
Process Production Quality Prediction Algorithm Based on Mar-G LSTM

Paper Title Process Production Quality Prediction Algorithm Based on Mar-G LSTM Authors Yin Yanchao, Su Yifan (Corresponding Author), Tang Jun, Lin Wenqiang, Pu Haoran, Wang Linyu Affiliations 1. School of Mechanical and Electrical Engineering, Kunming University of Science and Technology 2. Yunnan Tobacco Industrial Co., Ltd. Funding National Key R&D Program of China (2023YFB3308401) National … Read more

Why LSTM Is So Effective?

by
Why LSTM Is So Effective?

Follow the public account “ML_NLP“ Set as “Starred“, heavy content delivered first time! From | Zhihu Address | https://www.zhihu.com/question/278825804/answer/402634502 Author | Tian Yu Su Editor | Machine Learning Algorithms and Natural Language Processing Public Account This article is for academic sharing only. If there is an infringement, please contact the background for deletion. I have … Read more

Understanding LSTM and GRU in Gated Recurrent Neural Networks

by
Understanding LSTM and GRU in Gated Recurrent Neural Networks

Click on the above “Beginner’s Guide to Visual Learning” to choose to add “Star” or “Top” Heavyweight content delivered at the first time Editor | Anke Produced by | Panchuang AI Technology Team Table of Contents: Introduction to Gated Recurrent Neural Networks Long Short-Term Memory Networks (LSTM) Gated Recurrent Units (GRU) Implementing LSTM and GRU … Read more

Overview of Deep Learning Models and Their Principles

by
Overview of Deep Learning Models and Their Principles

Originally from Python AI Frontiers This article systematically and comprehensively organizes the introduction and algorithm principles of various deep learning models. 1 Main Text Deep learning methods utilize neural network models for advanced pattern recognition and automatic feature extraction, achieving significant results in the field of data mining in recent years. Common models include not … Read more

A Comprehensive Guide to Understanding RNN Family

by
A Comprehensive Guide to Understanding RNN Family

Follow our WeChat public account “ML_NLP“ Set as “Starred“, heavy content delivered to you first! Author | Yu Wenyu Source | See the end of the article for “Read the original text” Organizer | NewBeeNLP WeChat public account BERT is great, but don’t forget our old friend RNN! Introduction CNN (Convolutional Neural Network) and RNN … Read more

Introduction to RNN in DI-engine Reinforcement Learning

by
Introduction to RNN in DI-engine Reinforcement Learning

1. Introduction to RNN Recurrent Neural Network (RNN) is a type of neural network used for processing sequential data. Unlike traditional feedforward neural networks, RNN introduces an “internal state” (also known as “hidden state”), which allows the network to store past information and use it to influence subsequent outputs. The updating process of this internal … Read more

Comprehensive Overview of RNN (Recurrent Neural Networks)

by
Comprehensive Overview of RNN (Recurrent Neural Networks)

Introduction to Recurrent Neural Networks Why RNN After BP Algorithm and CNN? Upon reflection on the BP algorithm and CNN (Convolutional Neural Networks), we find that their outputs only consider the influence of the previous input without taking into account the influence of inputs at other times. For instance, recognizing single objects like cats, dogs, … Read more