Zobrazeno 1 - 10
of 403
pro vyhledávání: '"Chen, Haoyuan"'
Autor:
Chen, Haoyuan, Tuo, Rui
Gaussian process (GP) models have received increasingly attentions in recent years due to their superb prediction accuracy and modeling flexibility. To address the computational burdens of GP models for large-scale datasets, distributed learning for
Externí odkaz:
http://arxiv.org/abs/2408.00955
Autor:
Chen, Haoyuan, Tuo, Rui
Gaussian processes (GPs) are widely used in non-parametric Bayesian modeling, and play an important role in various statistical and machine learning applications. In a variety tasks of uncertainty quantification, generating random sample paths of GPs
Externí odkaz:
http://arxiv.org/abs/2408.00206
Autor:
Li, Shuang, Li, Guoqing, Liu, Ying, Xu, Wanying, Yang, Ningning, Chen, Haoyuan, Li, Ning, Luo, Kunpeng, Jin, Shizhu
Publikováno v:
Journal of Medical Internet Research, Vol 22, Iss 3, p e16233 (2020)
BackgroundEndoscopic examination is a popular and routine procedure for the diagnosis and treatment of gastrointestinal (GI) diseases. Skilled endoscopists are in great demand in clinical practice, but the training process for beginners to become end
Externí odkaz:
https://doaj.org/article/ce5f44f9339e4a70a201d3903b0d15c2
Models based on U-like structures have improved the performance of medical image segmentation. However, the single-layer decoder structure of U-Net is too "thin" to exploit enough information, resulting in large semantic differences between the encod
Externí odkaz:
http://arxiv.org/abs/2309.03686
Among generalized additive models, additive Mat\'ern Gaussian Processes (GPs) are one of the most popular for scalable high-dimensional problems. Thanks to their additive structure and stochastic differential equation representation, back-fitting-bas
Externí odkaz:
http://arxiv.org/abs/2305.00324
Autor:
Shi, Liyu, Li, Xiaoyan, Hu, Weiming, Chen, Haoyuan, Chen, Jing, Fan, Zizhen, Gao, Minghe, Jing, Yujie, Lu, Guotao, Ma, Deguo, Ma, Zhiyu, Meng, Qingtao, Tang, Dechao, Sun, Hongzan, Grzegorzek, Marcin, Qi, Shouliang, Teng, Yueyang, Li, Chen
Background and Purpose: Colorectal cancer is a common fatal malignancy, the fourth most common cancer in men, and the third most common cancer in women worldwide. Timely detection of cancer in its early stages is essential for treating the disease. C
Externí odkaz:
http://arxiv.org/abs/2212.00532
Autor:
Chen, Haoyuan1,2 (AUTHOR) haoyuanchen123@gmail.com, Zhou, Sihang1 (AUTHOR) sihangjoe@gmail.com, Li, Kuan2 (AUTHOR) jpyin@dgut.edu.cn, Yin, Jianping2 (AUTHOR), Huang, Jian1 (AUTHOR) huang_jian@nudt.edu.cn
Publikováno v:
Mathematics (2227-7390). Oct2024, Vol. 12 Issue 19, p3061. 21p.
Autor:
Chen, Haoyuan1 (AUTHOR) haoyuanchen123@gmail.com, Han, Yufei1 (AUTHOR), Yao, Linwei1 (AUTHOR), Wu, Xin1 (AUTHOR), Li, Kuan1 (AUTHOR) likuan@dgut.edu.cn, Yin, Jianping1 (AUTHOR)
Publikováno v:
Mathematics (2227-7390). Oct2024, Vol. 12 Issue 19, p2996. 19p.
Autor:
Chen, Haoyuan
Ziel dieser Arbeit ist es, robuste und performante Algorithmen für die Fusion von polizeilichen Unfalldaten zur Testszenariengenerierung im Rahmen der Absicherung automatisierter Fahrfunktionen zu generieren. In dieser Arbeit werden dabei Methoden z
Externí odkaz:
https://tud.qucosa.de/id/qucosa%3A76495
https://tud.qucosa.de/api/qucosa%3A76495/attachment/ATT-0/
https://tud.qucosa.de/api/qucosa%3A76495/attachment/ATT-0/
Autor:
Chen, Haoyuan, Li, Chen, Li, Xiaoyan, Rahaman, Md Mamunur, Hu, Weiming, Li, Yixin, Liu, Wanli, Sun, Changhao, Sun, Hongzan, Huang, Xinyu, Grzegorzek, Marcin
Publikováno v:
Computers in Biology and Medicine, Volume 143, April 2022, 105265
In recent years, colorectal cancer has become one of the most significant diseases that endanger human health. Deep learning methods are increasingly important for the classification of colorectal histopathology images. However, existing approaches f
Externí odkaz:
http://arxiv.org/abs/2206.03368