Artificial Neural Networks

Stanford Chinese Professor: Sound Waves and Light Waves Are Actually RNNs!

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Stanford Chinese Professor: Sound Waves and Light Waves Are Actually RNNs!

Recently, the intersection of physics, mathematics, and machine learning has promoted the use of machine learning frameworks to optimize physical models, further encouraging researchers to develop many exciting new machine learning models (such as Neural ODEs, Hamiltonian Neural Networks, etc.) that draw on concepts from physics. Researchers from Stanford University’s Shanhui Fan group are particularly … Read more

Understanding LSTM: A Comprehensive Guide

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Understanding LSTM: A Comprehensive Guide

Friends familiar with deep learning know that LSTM is a type of RNN model that can conveniently handle time series data and is widely used in fields such as NLP. After watching Professor Li Hongyi’s deep learning videos from National Taiwan University, especially the first part introducing RNN and LSTM, I felt enlightened. This article … Read more

Understanding LSTM for Elementary Students

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Understanding LSTM for Elementary Students

Source: Machine Learning Algorithms Explained Friends familiar with deep learning know that LSTM is a type of RNN model that can conveniently handle time series data and is widely used in fields such as NLP. After watching Professor Li Hongyi’s deep learning videos from National Taiwan University, especially the first part introducing RNN and LSTM, … Read more

Exploring Attention as Square Complexity RNN

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Exploring Attention as Square Complexity RNN

This article is approximately 3900 words long and is recommended for an 8-minute read. In this article, we demonstrate that Causal Attention can be rewritten in the form of an RNN. In recent years, RNNs have rekindled interest among researchers and users due to their linear training and inference efficiency, hinting at a “Renaissance” in … Read more

RNN Learns Suitable Hidden Dimensions with White Noise

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RNN Learns Suitable Hidden Dimensions with White Noise

Abstract Neural networks need the right representations of input data to learn. Recently published in Nature Machine Intelligence, a new study examines how gradient learning shapes a fundamental property of representations in recurrent neural networks (RNNs)—their dimensionality. Through simulations and mathematical analysis, the study demonstrates how gradient descent guides RNNs to compress the dimensionality of … Read more

How to Create RNN Directly from NumPy

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How to Create RNN Directly from NumPy

Click on the above“Beginner’s Guide to Vision” to choose to add Star or Pin. Important content delivered promptly Mu Yi from A Fei Temple From | Quantum Bits Using mature frameworks like Tensorflow and PyTorch to implement Recurrent Neural Networks (RNNs) has greatly lowered the technical barriers to entry. However, for beginners, this is still … Read more

Understanding RNN (Recurrent Neural Networks) Basics

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Understanding RNN (Recurrent Neural Networks) Basics

Click the “MLNLP” above and select “Star” for the public account Heavy content delivered first-hand Author | Yi Zhen Address | https://zhuanlan.zhihu.com/p/30844905 Column | Machine Learning Algorithms and Natural Language Processing Understanding RNN (Recurrent Neural Networks) Basics Basics of Neural Networks Neural networks can be considered as black boxes that can fit any function. As … Read more

Understanding RNN: Recurrent Neural Networks and Their PyTorch Implementation

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Understanding RNN: Recurrent Neural Networks and Their PyTorch Implementation

Click on the above “Visual Learning for Beginners” to choose to add a Star or “Pin” Heavyweight content delivered first-hand From | Zhihu Author | Lucas Link | https://zhuanlan.zhihu.com/p/85995376 Understanding RNN: Recurrent Neural Networks and Their PyTorch Implementation Recurrent Neural Networks (RNN) are a type of neural network with short-term memory capabilities. Specifically, the network … Read more

Understanding DNN, RNN, CNN: Key Neural Network Concepts

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Understanding DNN, RNN, CNN: Key Neural Network Concepts

“Lookalikes” have always been a big joke in the entertainment industry. If you run into Sun Nan, Yang Chenggang, Wang Daye… while buying a train ticket, face-blindness sufferers might as well give up going home and cry on the spot. Of course, “lookalikes” are not unique to the entertainment industry; there are also some “similar-looking” … Read more

The Relationship Between CNN and RNN

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The Relationship Between CNN and RNN

Click the above“Beginner’s Guide to Vision” to choose to add Starred or “Top” Essential Knowledge Delivered First-Hand 1. Introduction to CNN CNN is a type of neural network that utilizes convolutional calculations. It can preserve the main features of a large image by reducing it to a smaller pixel image through convolutional calculations. This article … Read more