时间序列应用的扩散模型:调查

IF 2.7 3区 工程技术 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Frontiers of Information Technology & Electronic Engineering Pub Date : 2023-12-28 DOI:10.1631/fitee.2300310
Lequan Lin, Zhengkun Li, Ruikun Li, Xuliang Li, Junbin Gao
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引用次数: 0

摘要

扩散模型是基于深度学习的生成模型系列,在前沿机器学习研究中的地位日益突出。扩散模型在生成与观测数据相似的样本方面表现出色,如今已广泛应用于图像、视频和文本合成。近年来,扩散的概念已被扩展到时间序列应用中,并开发出许多功能强大的模型。考虑到缺乏对这些模型的方法总结和论述,我们提供了这份调查报告,作为该领域新研究人员的基础资料,并为未来研究提供灵感。为了让读者更好地理解,我们对扩散模型的基础知识进行了介绍。除此以外,我们主要关注基于扩散的时间序列预测、估算和生成方法,并在三个章节中分别介绍了这些方法。我们还对同一应用的不同方法进行了比较,并酌情强调了它们之间的联系。最后,我们总结了基于扩散的方法的共同局限性,并强调了潜在的未来研究方向。
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Diffusion models for time-series applications: a survey

Diffusion models, a family of generative models based on deep learning, have become increasingly prominent in cutting-edge machine learning research. With distinguished performance in generating samples that resemble the observed data, diffusion models are widely used in image, video, and text synthesis nowadays. In recent years, the concept of diffusion has been extended to time-series applications, and many powerful models have been developed. Considering the deficiency of a methodical summary and discourse on these models, we provide this survey as an elementary resource for new researchers in this area and to provide inspiration to motivate future research. For better understanding, we include an introduction about the basics of diffusion models. Except for this, we primarily focus on diffusion-based methods for time-series forecasting, imputation, and generation, and present them, separately, in three individual sections. We also compare different methods for the same application and highlight their connections if applicable. Finally, we conclude with the common limitation of diffusion-based methods and highlight potential future research directions.

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来源期刊
Frontiers of Information Technology & Electronic Engineering
Frontiers of Information Technology & Electronic Engineering COMPUTER SCIENCE, INFORMATION SYSTEMSCOMPU-COMPUTER SCIENCE, SOFTWARE ENGINEERING
CiteScore
6.00
自引率
10.00%
发文量
1372
期刊介绍: Frontiers of Information Technology & Electronic Engineering (ISSN 2095-9184, monthly), formerly known as Journal of Zhejiang University SCIENCE C (Computers & Electronics) (2010-2014), is an international peer-reviewed journal launched by Chinese Academy of Engineering (CAE) and Zhejiang University, co-published by Springer & Zhejiang University Press. FITEE is aimed to publish the latest implementation of applications, principles, and algorithms in the broad area of Electrical and Electronic Engineering, including but not limited to Computer Science, Information Sciences, Control, Automation, Telecommunications. There are different types of articles for your choice, including research articles, review articles, science letters, perspective, new technical notes and methods, etc.
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