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pro vyhledávání: '"Kim, Kai"'
Autor:
Kim, Kai, Tsai, Howard, Sen, Rajat, Das, Abhimanyu, Zhou, Zihao, Tanpure, Abhishek, Luo, Mathew, Yu, Rose
Current forecasting approaches are largely unimodal and ignore the rich textual data that often accompany the time series due to lack of well-curated multimodal benchmark dataset. In this work, we develop TimeText Corpus (TTC), a carefully curated, t
Externí odkaz:
http://arxiv.org/abs/2411.06735
Multi-fidelity surrogate modeling aims to learn an accurate surrogate at the highest fidelity level by combining data from multiple sources. Traditional methods relying on Gaussian processes can hardly scale to high-dimensional data. Deep learning ap
Externí odkaz:
http://arxiv.org/abs/2402.18846
Publikováno v:
Journal of Basic Design & Art. 21:489-504
Autor:
Joo Young Leem, Kim, Kai Chun
Publikováno v:
Journal of Basic Design & Art. 21:347-358
Autor:
Lee, DonHee1 dhlee@kmu.ac.kr, Kim, Kai1 kkim1@bryant.edu
Publikováno v:
International Journal of Quality Innovation. 1/25/2017, Vol. 3 Issue 1, p1-15. 15p.
Autor:
Pan, Kim Kai-tien
Thesis (M.S.)--University of Wisconsin--Madison, 1975.
eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references.
eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references.
Externí odkaz:
http://catalog.hathitrust.org/api/volumes/oclc/53791062.html
Akademický článek
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