Introduction Graph Learning is a machine learning method that studies and applies graph-structured data. In graph learning, data is represented as a graph consisting of nodes and edges, where nodes represent entities or objects, and edges represent the relationships or connections between them. Therefore, graph learning is particularly suitable for multi-scale analysis, modeling, and simulation … Read more
Research Progress on Multimodal Named Entity Recognition Methods Wang Hairong1,2, Xu Xi1, Wang Tong1, Jing Boxiang1 1. School of Computer Science and Engineering, Northern Minzu University; 2. Key Laboratory of Intelligent Processing of Image and Graphics, Northern Minzu University Click “Read the Original” at the end of the article to view the literature! Table of … Read more
MLNLP community is a well-known machine learning and natural language processing community both domestically and internationally, covering audiences including NLP master’s and PhD students, university professors, and corporate researchers. The Vision of the Community is to promote communication and progress between the academic and industrial circles of natural language processing and machine learning, especially for … Read more
Click on the above“Beginner Learning Vision”, select to addStar or “Top” Heavy content delivered immediately From | Zhihu Author丨Xiao Xi learns every day Link丨https://zhuanlan.zhihu.com/p/152234745 Introduction Multimodal deep learning mainly includes three aspects: multimodal learning representation, multimodal signal fusion, and multimodal applications. This article focuses on related fusion methods in computer vision and natural language processing, … Read more
First, I recommend a Jupyter environment, which is provided by Google called colab (https://colab.research.google.com/), where you can use free GPUs. The first time you use it, you need to download the relevant Python libraries in the experimental environment. !pip install torch!pip install torchtext!python -m spacy download en Our preliminary idea is to first input a … Read more
Introduction The main content of this article is poetry generation based on LSTM, which includes an introduction to the dataset, experimental code, and results. The experiment uses a Long Short-Term Memory (LSTM) deep learning model, trained for 10 epochs. During the testing process, poetry generation results are produced at each epoch, and as the epochs … Read more
Follow the public account “ML_NLP“ Set as “Starred“, heavy content delivered first time! From | Zhihu Address | https://www.zhihu.com/question/278825804/answer/402634502 Author | Tian Yu Su Editor | Machine Learning Algorithms and Natural Language Processing Public Account This article is for academic sharing only. If there is an infringement, please contact the background for deletion. I have … Read more
Follow the official account “ML_NLP“ Set as “Starred“, delivering heavy content immediately! Source | Zhihu Address | https://zhuanlan.zhihu.com/p/97378498 Author | Si Jie’s Portable Mattress Editor | Machine Learning Algorithms and Natural Language Processing Official Account This article is authorized by the author, secondary reproduction is prohibited Modules and functions needed: import torch import torch.nn as … Read more
Follow us on WeChat “ML_NLP” Set as “Starred”, delivering valuable content to you first! Produced by Machine Learning Algorithms and Natural Language Processing Original Column Author on WeChat @ Yi Zhen School | PhD Student at Harbin Institute of Technology SCIR 1. Why RNN Needs to Handle Variable Length Inputs Assuming we have an example … Read more
This article is approximately 2600 words long and is recommended to be read in 9 minutes. The SUPRA method significantly improves model stability and performance by replacing softmax normalization with GroupNorm. Transformers have established themselves as the primary model architecture, particularly due to their outstanding performance across various tasks. However, the memory-intensive nature of Transformers … Read more