Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Lu, Jiecheng"'
We propose an Autoregressive (AR) Moving-average (MA) attention structure that can adapt to various linear attention mechanisms, enhancing their ability to capture long-range and local temporal patterns in time series. In this paper, we first demonst
Externí odkaz:
http://arxiv.org/abs/2410.03159
Recent Transformer-based large language models (LLMs) demonstrate in-context learning ability to perform various functions based solely on the provided context, without updating model parameters. To fully utilize the in-context capabilities in time s
Externí odkaz:
http://arxiv.org/abs/2405.14982
For Multivariate Time Series Forecasting (MTSF), recent deep learning applications show that univariate models frequently outperform multivariate ones. To address the difficiency in multivariate models, we introduce a method to Construct Auxiliary Ti
Externí odkaz:
http://arxiv.org/abs/2403.01673
Long-term time series forecasting (LTSF) is important for various domains but is confronted by challenges in handling the complex temporal-contextual relationships. As multivariate input models underperforming some recent univariate counterparts, we
Externí odkaz:
http://arxiv.org/abs/2310.09488
Publikováno v:
Acoustical Imaging ISBN: 9781461362869
Based upon the correlation between interior flaw and parameters such as ultrasonic velocity, the first ultrasonic amplitude and the received ultrasonic frequency, a microcomputer testing system has been developed, which comprises of three elementary
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d1fbe7d2f1e178f97f6ec51ca98e811f
https://doi.org/10.1007/978-1-4615-2958-3_28
https://doi.org/10.1007/978-1-4615-2958-3_28
Publikováno v:
MRS Online Proceedings Library; 2003, Vol. 804 Issue 1, p323-327, 5p
Akademický článek
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Publikováno v:
Progress in Natural Science. Aug99, Vol. 9 Issue 8, p623. 7p. 1 Chart, 2 Graphs.
Conference
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