Zobrazeno 1 - 10
of 24
pro vyhledávání: '"Liao, Shujian"'
Autor:
Zhang, Yuanyuan, Tong, Congcong, Lv, Xing, Lou, Shiye, Liao, Shujian, Feng, Jiaxing, Liu, Lili, Zhang, DongEn, Zhang, Jinghong, Shi, Linxing
Publikováno v:
In Separation and Purification Technology 19 February 2025 354 Part 4
In this paper, we investigate the problem of predicting the future volatility of Forex currency pairs using the deep learning techniques. We show step-by-step how to construct the deep-learning network by the guidance of the empirical patterns of the
Externí odkaz:
http://arxiv.org/abs/2112.01166
Synthetic data is an emerging technology that can significantly accelerate the development and deployment of AI machine learning pipelines. In this work, we develop high-fidelity time-series generators, the SigWGAN, by combining continuous-time stoch
Externí odkaz:
http://arxiv.org/abs/2111.01207
This paper contributes to the challenge of skeleton-based human action recognition in videos. The key step is to develop a generic network architecture to extract discriminative features for the spatio-temporal skeleton data. In this paper, we propos
Externí odkaz:
http://arxiv.org/abs/2110.13008
Generative adversarial networks (GANs) have been extremely successful in generating samples, from seemingly high dimensional probability measures. However, these methods struggle to capture the temporal dependence of joint probability distributions i
Externí odkaz:
http://arxiv.org/abs/2006.05421
Autor:
Zhang, Yuanyuan, Tong, Congcong, Shi, Linxing, Yin, You, Lou, Shiye, Liu, Jiawei, Liao, Shujian, Liu, Lili, Zhang, DongEn
Publikováno v:
In Applied Surface Science 30 November 2023 638
This paper contributes to the challenge of learning a function on streamed multimodal data through evaluation. The core of the result of our paper is the combination of two quite different approaches to this problem. One comes from the mathematically
Externí odkaz:
http://arxiv.org/abs/1908.08286
Akademický článek
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Akademický článek
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Autor:
Liao, Shujian1,2 (AUTHOR), Yang, Chenbo1,2 (AUTHOR), Li, Dengao2,3 (AUTHOR) lidengao@tyut.edu.cn
Publikováno v:
PLoS ONE. 1/19/2021, Vol. 16 Issue 1, p1-12. 12p.