Understanding Convolutional Neural Networks (CNN) Convolutional Neural Networks (CNN) are a type of feedforward neural network where artificial neurons can respond to a portion of the surrounding units within a coverage area, demonstrating outstanding performance in large image processing. CNN has five characteristics: 1. Local perception; 2. Parameter sharing; 3. Sampling; 4. Multiple convolutional kernels; … Read more
I am a master’s student at a double first-class university, and I am currently preparing for the 2024 autumn recruitment. While looking for internships in large model algorithm positions, I encountered many interesting interviews, so I decided to record these interview questions and share them with friends who, like me, are striving for a satisfactory … Read more
New Intelligence Report Source: Reddit, Science Editors: Daming, Pengfei [New Intelligence Guide]Recently, Stanford University Chinese Professor Shanhui Fan’s team published an article in a sub-journal of Science, pointing out that whether it is sound waves, light waves, or other forms of waves, their descriptive equations can be equivalent to Recurrent Neural Networks (RNNs). This discovery … Read more
Selected from Reddit Author: Ian Williamson Translated by Machine Heart Contributors: Wang Zhi Jia, Mo Wang A study from Stanford University found a correspondence between waves in physics and computations in RNNs. Paper link:https://advances.sciencemag.org/content/5/12/eaay6946 GitHub link:https://github.com/fancompute/wavetorch Recently, there has been a lot of exciting interaction between machine learning and some fields of physics and numerical … Read more
Selected from Medium Author: Eugenio Culurciello Translation by Machine Heart Contributors: Liu Xiaokun, Siyuan The author states: We have been trapped in the pit of RNNs, LSTMs, and their variants for many years; it is time to abandon them! In 2014, RNNs and LSTMs were revived. We all read Colah’s blog “Understanding LSTM Networks” and … Read more
Convolutional Neural Networks and Recurrent Neural Networks are widely used in machine learning today. However, they are typically used for completely different use cases. What are the principles and differences of CNN and RNN in artificial intelligence? In machine learning, each type of artificial neural network is tailored for specific tasks. Below, we will introduce … Read more
Regarding the calculation of RNN parameters, the PPT does not explain it very clearly, as it only contains images without text. At the same time, the textbook version by Qizhi Yao does not provide any exercises related to RNN parameter calculation, and the final exam may only test based on the descriptions in the images, … Read more
Recently, the Google Translate that has been spreading like wildfire among friends has achieved stunning performance. The core technology here is RNN – the so-called Recurrent Neural Network. RNN can be regarded as one of the most promising tools in deep learning’s future. Do you want to understand the source of its power? Do you … Read more
Selected from ArXiv Authors: Bo-Jian Hou, Zhi-Hua Zhou Contributors: Si Yuan, Xiao Kun This article is authorized for reproduction by Almost Human (almosthuman2014) Reproduction is prohibited Apart from numerical calculations, do you really know what neural networks are doing internally? We have always understood deep models based on their computational flow, but we are still … Read more
Editor: We have a user who enjoys using machine learning to experiment with strategies. His descriptions of several models are quite vivid, and he has written a demo strategy using PonderLSTM, which we are sharing today~ The ACT model simulates the thinking process of complex problems by performing multiple computations at each time step (time … Read more