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Transformers in Time-Series Analysis: A Tutorial
Circuits, Systems, and Signal Processing, 2023 Transformer architecture has widespread applications, particularly in Natural Language Processing and computer vision. Recently Transformers have been employed in various aspects of time-series analysis. This tutorial provides an overview of the Transformer architecture, its applications, and a collection of examples from recent research papers in time-
Sabeen Ahmed +5 more
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TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis [PDF]
International Conference on Learning Representations, 2022 Time series analysis is of immense importance in extensive applications, such as weather forecasting, anomaly detection, and action recognition. This paper focuses on temporal variation modeling, which is the common key problem of extensive analysis ...
Haixu Wu +5 more
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Self-Supervised Learning for Time Series Analysis: Taxonomy, Progress, and Prospects [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023 Self-supervised learning (SSL) has recently achieved impressive performance on various time series tasks. The most prominent advantage of SSL is that it reduces the dependence on labeled data.
Kexin Zhang +10 more
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Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences, 1998 A new method for analysing nonlinear and non-stationary data has been developed. The key part of the method is the ‘empirical mode decomposition’ method with which any complicated data set can be decomposed into a finite and often small number of ...
Norden E. Huang +8 more
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Exploring Progress in Multivariate Time Series Forecasting: Comprehensive Benchmarking and Heterogeneity Analysis [PDF]
IEEE Transactions on Knowledge and Data Engineering, 2023 Multivariate Time Series (MTS) analysis is crucial to understanding and managing complex systems, such as traffic and energy systems, and a variety of approaches to MTS forecasting have been proposed recently.
Zezhi Shao +11 more
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Language time series analysis [PDF]
Physica A: Statistical Mechanics and its Applications, 2006 21 pages, 5 figures, accepted in Physica ...
Kosmidis, Kosmas +2 more
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Statistics for Environmental Science and Management, 2003 In the previous chapter we considered the dependence of a random variable y on a controlled variable t. As in that case we will assume here that y consists of two parts, the true value of the measured quantity η and a measurement error \(\varepsilon\),
S. Brandt
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Time-series analysis with smoothed Convolutional Neural Network
Journal of Big Data, 2022 CNN originates from image processing and is not commonly known as a forecasting technique in time-series analysis which depends on the quality of input data. One of the methods to improve the quality is by smoothing the data.
Aji Prasetya Wibawa +5 more
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Lancet psychiatry, 2021 Background The COVID-19 pandemic is having profound mental health consequences for many people. Concerns have been expressed that, at their most extreme, these consequences could manifest as increased suicide rates. We aimed to assess the early effect of
J. Pirkis +68 more
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EntropyHub: An open-source toolkit for entropic time series analysis
PLoS ONE, 2021 An increasing number of studies across many research fields from biomedical engineering to finance are employing measures of entropy to quantify the regularity, variability or randomness of time series and image data.
M. Flood, Bernd Grimm
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