Bidirectional RNN

Do We Still Need Attention in Transformers?

by
Do We Still Need Attention in Transformers?

Selected from interconnects Author: Nathan Lambert Translated by Machine Heart Machine Heart Editorial Team State-space models are on the rise; has attention reached its end? In recent weeks, there has been a hot topic in the AI community: implementing language modeling with attention-free architectures. In short, this refers to a long-standing research direction in the … Read more

Future Frame Prediction in 2D Movie MR Images Using PCA and RNN

by
Future Frame Prediction in 2D Movie MR Images Using PCA and RNN

✅Author Bio: A Matlab simulation developer passionate about research, skilled in data processing, modeling simulation, program design, complete code acquisition, paper reproduction, and scientific simulation. 🍎Personal Homepage:Matlab Research Studio 🍊Personal Motto: Seek knowledge through inquiry; feel free to message me for help. 🔥 Content Introduction Abstract: Respiratory motion in medical imaging is a critical factor … Read more

RNN Transformation Mechanism and Practical Applications

by
RNN Transformation Mechanism and Practical Applications

Follow Hui Kuo Technology to learn more about technology knowledge Hello everyone, I am Liu Zenghui! Today we will continue the series of lectures on artificial intelligence neural networks, focusing on the transformation mechanism and practical applications of RNNs, exploring how they are widely used in various fields! Transformation Mechanism of RNN In the previous … Read more

When RNN Meets Reinforcement Learning: Building General Models for Space

by
When RNN Meets Reinforcement Learning: Building General Models for Space

You may be familiar with reinforcement learning, and you may also know about RNNs. What sparks can these two relatively complex concepts in the world of machine learning create together? Let me share a few thoughts. Before discussing RNNs, let’s first talk about reinforcement learning. Reinforcement learning is gaining increasing attention; its importance can be … Read more

Understanding the Mathematical Principles Behind RNNs

by
Understanding the Mathematical Principles Behind RNNs

0Introduction Nowadays, discussions about machine learning, deep learning, and artificial neural networks are becoming more and more prevalent. However, programmers often just want to use these magical frameworks without wanting to know how they actually work behind the scenes. But if we could grasp these underlying principles, wouldn’t it be better for us to use … Read more

Using RNN for Long-Term Time Series Forecasting

by
Using RNN for Long-Term Time Series Forecasting

↑↑↑ Follow for “Star Mark“Kaggle Competition Guide Kaggle Competition Guide Author: Fareise, excerpted from Yuan Yuan’s Algorithm Notes Using RNN for Long-Term Time Series Forecasting, Is It Better Than Transformer SOTA? This article introduced today comes from South China University of Technology, proposing an RNN-based long-term time series forecasting model that outperforms the SOTA Transformer … Read more

Do RNN and LSTM Have Long-Term Memory?

by
Do RNN and LSTM Have Long-Term Memory?

This article introduces the ICML 2020 paper “Do RNN and LSTM have Long Memory?“. The authors of the paper are from Huawei Noah’s Ark Lab and the University of Hong Kong.. Author | Noah’s Ark Lab Editor | Cong Mo Paper link: https://arxiv.org/abs/2006.03860 1 Introduction To overcome the difficulties of Recurrent Neural Networks (RNNs) in … Read more

Four Structures of RNN

by
Four Structures of RNN

Starting the Journey of RNN, Commonly Known Four Structures of RNN One to One: This is the traditional application of neural networks, usually used for simple input to output tasks. For example, in image classification, the network receives an image as input and identifies the category of the object represented in the image. Specifically, suppose … Read more