Deep Learning for Time Series Classification and Extrinsic Regression: A Current Survey

2023-02-06 · Navid Mohammadi Foumani, Lynn Miller, Chang Wei Tan, Geoffrey I. Webb, Germain Forestier, Mahsa Salehi

Time Series Classification and Extrinsic Regression are important and challenging machine learning tasks. Deep learning has revolutionized natural language processing and computer vision and holds great promise in other fields such as time series analysis where the relevant features must often be abstracted from the raw data but are not known a priori. This paper surveys the current state of the art in the fast-moving field of deep learning for time series classification and extrinsic regression. We review different network architectures and training methods used for these tasks and discuss the challenges and opportunities when applying deep learning to time series data. We also summarize two critical applications of time series classification and extrinsic regression, human activity recognition and satellite earth observation.

📄 PDF Abstract BibTeX arXiv:2302.02515

Code (1)

navidfoumani/tsc_survey 공식 구현 pytorch

Tasks

Activity Recognition ClassificationDeep LearningEarth ObservationHuman Activity Recognition regressionTime SeriesTime Series Analysis Time Series Classification

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High-dimensional time series data poses challenges due to its dynamic nature, varying lengths, and presence of missing values. This kind of data requires extensive preprocessing, limiting the applicability of existing Ti…

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regression Time Series Time Series Analysis Time Series Classification+2

Monash University, UEA, UCR Time Series Extrinsic Regression Archive

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Time series research has gathered lots of interests in the last decade, especially for Time Series Classification (TSC) and Time Series Forecasting (TSF). Research in TSC has greatly benefited from the University of Cali…

Benchmarking Missing Values regression Time Series+4

Unsupervised Feature Based Algorithms for Time Series Extrinsic Regression

2023-05-02 · David Guijo-Rubio, Matthew Middlehurst, Guilherme Arcencio, Diego Furtado Silva 외

Time Series Extrinsic Regression (TSER) involves using a set of training time series to form a predictive model of a continuous response variable that is not directly related to the regressor series. The TSER archive for…

regression Time Series Time Series Classification

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The success of large language models (LLMs) for time series has been demonstrated in previous work. Utilizing a symbolic time series representation, one can efficiently bridge the gap between LLMs and time series. Howeve…

Time Series Time Series Classification Time Series Prediction Time Series Regression