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Are Transformers Effective for Time Series Forecasting? [PDF]
AAAI Conference on Artificial Intelligence, 2022 Recently, there has been a surge of Transformer-based solutions for the long-term time series forecasting (LTSF) task. Despite the growing performance over the past few years, we question the validity of this line of research in this work.
Ailing Zeng +3 more
semanticscholar +1 more source
A Time Series is Worth 64 Words: Long-term Forecasting with Transformers [PDF]
International Conference on Learning Representations, 2022 We propose an efficient design of Transformer-based models for multivariate time series forecasting and self-supervised representation learning. It is based on two key components: (i) segmentation of time series into subseries-level patches which are ...
Yuqi Nie +3 more
semanticscholar +1 more source
Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting [PDF]
AAAI Conference on Artificial Intelligence, 2020 Many real-world applications require the prediction of long sequence time-series, such as electricity consumption planning. Long sequence time-series forecasting (LSTF) demands a high prediction capacity of the model, which is the ability to capture ...
Haoyi Zhou +6 more
semanticscholar +1 more source
iTransformer: Inverted Transformers Are Effective for Time Series Forecasting [PDF]
International Conference on Learning Representations, 2023 The recent boom of linear forecasting models questions the ongoing passion for architectural modifications of Transformer-based forecasters. These forecasters leverage Transformers to model the global dependencies over temporal tokens of time series ...
Yong Liu +6 more
semanticscholar +1 more source
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
semanticscholar +1 more source
PLoS ONE, 2022 Eating disorders are associated with one of the highest mortality rates among all mental disorders, yet there is very little research about them within the newly emerging and promising field of computational psychiatry. As such, we focus on investigating
Jakub Onysk, Peggy Seriès
doaj +2 more sources
Journal of Orthopaedic Surgery and Research, 2021 Background Remarkably little research has been published on chronic exertional compartment syndrome (CECS) of the forearm. This study investigated forearm flexor compartment pressure pre- and post-exercise in elite motorbike racers clinically diagnosed ...
Dominic P. O’Dowd +6 more
doaj +1 more source
Celebrating 20 years of open access publishing at BMC Musculoskeletal Disorders
BMC Musculoskeletal Disorders, 2020 Twenty years ago, on October 23, the first article published by BMC Musculoskeletal Disorders appeared free online. Over 5700 publications later, we celebrate our anniversary as the largest Open Access journal in the ‘Orthopaedics and Sports Medicine ...
Ciarán Martin Fitzpatrick +1 more
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Harmonic series with polylogarithmic functions [PDF]
Vojnotehnički Glasnik, 2022 Introduction/purpose: Some sums of the polylogarithmic function associated with harmonic numbers are established. Methods: The approach is based on using the summation methods.
Vuk Stojiljković +2 more
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Trend analyses of regional time series of temperatures and rainfall of the Tapi basin
Journal of Agrometeorology, 2020 Climate change information at the scale of basin is vital for planning, development and use of water. The Tapi basin is climatically responsive. Hydrological response of a basin is based mainly on rainfall and temperature.
GANESH D. KALE
doaj +1 more source