前言今天再来做一个神经网络的分类任务,完整代码见 https://github.com/zong4/AILearning,同时专栏里所有的文章都会同步在我的个人博客 https://zong4.github.io。代码来看看比上次多了什么。 数据增强首先是考…
Today, almost all types of AI, including those used to build large language models and image recognition systems, include sub-networks known as a multilayer perceptron (MLP). In an MLP, artificial neurons are arranged in dense, interconnected “layers.” Each neuron has within it ...
Deep neural networks (DNNs) have found many useful applications in recent years. Of particular interest have been those instances where their successes imitate human cognition and many consider artificial intelligences to offer a lens for understanding human intelligence. Here, we criticize the ...
In this way, neural networks can perform tasks that would be impossible for humans. They sift through huge quantities of data at speed, highlighting patterns that may otherwise escape attention. It was our belief that we could use neural networks to train the most accurate and advanced handwritin...
Discover how we are innovating Graph Neural Networks in robustness, explainability, and dynamic graph analysis for a smarter, more robust AI.
为了解决这一挑战,AI 模型水印技术应运而生,其将多媒体数字水印技术的思想推广至人工智能领域,进而开创了一个全新的领域。2017年在 ICMR(CCF B)会议上发表的《Embedding Watermarks into Deep Neural Networks》是 AI 模型水印技术的开山之作。此文当年获得了 ICMR 会议的最佳论文候选,虽然没有斩获 ICMR 会议的...
Neural networks make many types of artificial intelligence (AI) possible. Large language models (LLMs) such as ChatGPT, AI image generators like DALL-E, and predictive AI models all rely to some extent on neural networks. How do neural networks work? Neural networks are composed of a collect...
Neural networks are the core software of deep learning. Even though they’re so widespread, however, they’re really poorly understood. Researchers have observed their emergent properties without actually understanding why they work the way they do. Now
until the system settles down into any local minimum of the energy surface,Hopfield 网络: 联想记忆,Hopfield网络的一个主要应用 基于与数据部分相似的输入,可以回想起数据本身(attractor state) 也称作内容寻址记忆(content-addressable memory,Stored Pattern,Memory Association,虞台文, Feedback Networksand ...
Transformers are enabling a variety of new AI applications and expanding the performance of many existing ones. "Not only have these networks demonstrated they can adapt to new domains and problems, they also can process more data in a shorter amount of time and with better accuracy," Sullivan...