Machine Heart Column This column is produced by Machine Heart SOTA! Model Resource Station, updated every Sunday on the Machine Heart public account. This column will review common tasks in natural language processing, computer vision, and other fields, and detail the classic models that have achieved SOTA on these tasks. Visit SOTA! Model Resource Station … Read more
Machine Heart Report Contributor: Siyuan With the popularity of frameworks like TensorFlow and PyTorch, building neural networks often just involves calling a few API lines. Most developers have become unfamiliar with the underlying mechanisms, especially how to implement neural networks using pure NumPy. Previously, Machine Heart introduced how to implement a simple convolutional neural network … Read more
Machine Heart Compilation Author: Sander Dieleman Editor: Panda W Diffusion models are very popular, and their descriptions vary widely. In this article, a DeepMind research scientist provides a comprehensive analysis of the topic “What is a diffusion model?” If you’ve tried one of the most popular AI painting tools, Stable Diffusion, then you’ve already experienced … Read more
Source | Zhihu Author | JerryFly Link | https://zhuanlan.zhihu.com/p/115823190 Editor | Deep Learning Matters WeChat Official Account This article is for academic exchange only. If there is any infringement, please contact us for deletion. RNN is commonly used to handle sequential problems. This article demonstrates the computation process of RNN using animated graphics. The three … Read more
Selected from arXiv Authors: Matthew MacKay et al. Translated by: Machine Heart Contributors: Gao Xuan, Zhang Qian Recurrent Neural Networks (RNNs) achieve the best current performance in processing sequential data, but they require a large amount of memory during training. Reversible Recurrent Neural Networks provide a way to reduce the memory requirements for training, as … Read more
Big Data Digest Production Source: Google Blog Compiled by: Mali The weather in spring can change faster than you can turn a page; one moment it’s sunny, the next moment there’s a raging storm. In fact, accurately predicting the weather weeks or even minutes in advance is a scientific challenge that has a broad impact … Read more
“Programming is the art of telling another human being what one wants the computer to do.” — Donald Knuth 📑Paper:A Survey of Neural Code Intelligence: Paradigms, Advances and Beyond 🔧GitHub:https://github.com/QiushiSun/NCISurvey Note: The authors of the paper are from Shanghai Artificial Intelligence Laboratory, The University of Hong Kong, National University of Singapore, East China Normal University, … Read more
Over 200 star enterprises and 20 top investors from renowned investment institutions participated! “New Intelligence Growth List” aims to discover innovative companies in the AI field with “tenfold growth in three years“, will the next wave of AI unicorns include you? Click read the original text for details! According to Lei Feng Network: Artificial intelligence … Read more
Introduction: Hello, readers of the “Beginner’s Data Learning” series! It has been a while. Google recently launched a neural network visualization teaching platform called “TensorFlow Playground”. You can now play with neural networks right in your browser! Isn’t that amazing? After trying it out with the beginner, you’ll definitely feel like, “Aha, this is what … Read more
1 Introduction Deep neural networks are composed of neurons organized into layers and interconnected, capturing their architecture through computation graphs, where neurons are represented as nodes and directed edges connect different layers of neurons. The performance of neural networks depends on their architecture, but there is currently a lack of systematic understanding of the relationship … Read more