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
Original link:https://medium.com/towards-artificial-intelligence/one-lego-at-a-time-explaining-the-math-of-how-neural-networks-learn-with-implementation-from-scratch-39144a1cf80 From:Yongyu Excerpted from Algorithm Notes https://github.com/omar-florez/scratch_mlp/ The author explains step by step the mathematical processes used in training a neural network from scratch. Neural networks are cleverly arranged linear and nonlinear modules. The above image describes some of the mathematical processes involved in training a neural network. We will explain this in the … Read more
Welcome to the special winter vacation premium column “High-Tech Lessons for Kids” launched by Science Popularization China! Artificial intelligence, as one of the most cutting-edge technologies today, is changing our lives at an astonishing pace. From smart voice assistants to self-driving cars, from AI painting to machine learning, it opens up a future full of … Read more
Follow the official account "ML-CVer" Set as "Star", DLCV messages will be delivered! Author丨mayiwei1998 Source丨GiantPandaCV Editor丨极市平台 Abstract Due to the network structures in many papers being embedded into code frameworks, the code tends to be redundant. The author of this article has organized and reproduced the core code based on Attention networks from recent years. … Read more
All Fans Say: “Why Didn’t You Follow Me Sooner!” Hello everyone, I am Canshi. In the field of deep learning, there are many technical terms that can be confusing when first encountered. As you read more, you gradually get the hang of it, but it still feels somewhat lacking. Today, we will discuss a technical … Read more
[GiantPandaCV Guide] In recent years, Attention-based methods have gained popularity in both academia and industry due to their interpretability and effectiveness. However, the network structures proposed in papers are often embedded within code frameworks for classification, detection, segmentation, etc., leading to redundancy in code. For beginners like me, it can be challenging to find the … Read more
“I found a bug in the attention formula, and no one has noticed it for eight years. All Transformer models, including GPT and LLaMA, are affected.” Recently, a statistical engineer named Evan Miller has stirred up a storm in the AI field with his statement. We know that the attention formula in machine learning is … Read more
Star ★TopPublic AccountLove you all♥ Author: Chuan Bai Translated by: 1+1=6 1 Introduction The financial market mainly deals with time series problems, and there are numerous algorithms and tools around time series forecasting. Today, we use CNN for regression-based prediction and compare it with some traditional algorithms to see how it performs. We focus on … Read more