Click the "Advanced Programming" above and select the "Star" public account Super valuable content delivered to you immediately!!! In this article, we will demonstrate how to build a simple three-layer neural network from scratch. Although we will not derive all the mathematical operations involved in detail, I will do my best to explain our approach … Read more
How Does Tesla Achieve City Autonomous Driving with Cameras? Written by | James Recently, Tesla updated its autonomous driving software to version 2020.12, which includes the automatic recognition of traffic lights and stop signs. If Tesla is equipped with the FSD full self-driving capability package, it can experience the autonomous driving feature of stopping at … Read more
Technical Column Author: Liu Zhongyu Edited by Luobotu Today, I want to share with you about Graph Convolutional Networks. With the development of artificial intelligence, many people have heard of concepts like machine learning, deep learning, and convolutional neural networks. However, Graph Convolutional Networks are not often mentioned. So, what are Graph Convolutional Networks? Simply … Read more
Click the image for details↑ Human vision is an extraordinary ability. Although it has evolved over millions of years in specific environments, it can accomplish tasks that early visual systems have never experienced. Reading is a great example, such as recognizing cars, airplanes, road signs, and other man-made objects. However, the visual system also has … Read more
Graph neural networks (GNNs) have gained widespread attention and are applied in scenarios such as recommendation systems, knowledge graphs, and traffic analysis due to their advantages in handling non-Euclidean space data and complex features. The irregularity of large-scale graph structures, the complexity of node features, and the dependency of training samples put immense pressure on … Read more
As the next generation of advanced computing technology, quantum computers are on the brink of practical application. A landmark milestone was Google’s demonstration of quantum supremacy in 2019 using a 54-qubit superconducting quantum processor [1]. Since then, how to utilize quantum computing devices to solve real-world problems and achieve performance surpassing classical computers under existing … Read more
Resource Sharing Edited by: Rabbit Unknowingly, 2019 is about to pass Time flies, and you have accompanied us for another year This year We have compiled 33 papers and 165 news updates Prepared 46 paper interpretations Shared 38 pieces of technical content Held 6 sessions of AI Talking And organized 1 offline salon called “Graph … Read more
Selected from arXiv Compiled by Machine Heart Contributors: Jiang Siyuan, Smith, Li Yazhou Recently, a paper titled “Self-Normalizing Neural Networks” published on arXiv has garnered significant attention in the community. It introduces the Scaled Exponential Linear Unit (SELU), which brings in a self-normalizing property. This unit mainly uses a function g to map the mean … Read more
Selected from arXiv Compiled by Machine Heart Contributors: Jane W, Wu Pan Neuromorphic computing is considered an important direction for future artificial intelligence computing. Recently, several researchers from the Institute of Electrical and Electronics Engineers (IEEE) jointly published an 88-page overview paper that comprehensively reviews the development of neuromorphic computing over the past 35 years … Read more
Selected by OpenAI Author: JAKOB FOERSTER Translation by Machine Heart Using linear networks for nonlinear computation is an unconventional approach. Recently, OpenAI published a blog introducing their new research on deep linear networks, which do not use activation functions, yet achieve 99% training accuracy and 96.7% testing accuracy on MNIST. This new research has reignited … Read more