Zobrazeno 1 - 10
of 1 211
pro vyhledávání: '"Lu, Weiguo"'
Autor:
Zhou, Banghao, Guo, Lixiang, Lu, Weiguo, Rahman, Mahbubur, Zhang, Rongxiao, Chirayath, Varghese Anto, Park, Yang Kyun, Stojadinovic, Strahinja, Garza, Marvin, Wang, Ken Kang-Hsin
Background: FLASH radiotherapy is a treatment regime that delivers therapeutic dose to tumors at an ultra-high dose rate while maintaining adequate normal tissue sparing. However, a comprehensive understanding of the underlying mechanisms, potential
Externí odkaz:
http://arxiv.org/abs/2408.15426
Autor:
Li, Shuqi, Wu, Tianya, Huang, Xinhui, Zhou, Jia, Yan, Ziyue, Wang, Wei, Zeng, Hao, Hu, Yiming, Zhang, Xiaoxu, Liang, Zhijun, Wei, Wei, Zhang, Ying, Wei, Xiaomin, Zhang, Lei, Qi, Ming, Hu, Jun, Fu, Jinyu, Zhang, Hongyu, Li, Gang, Wu, Linghui, Dong, Mingyi, Li, Xiaoting, Casanova, Raimon, Zhang, Liang, Dong, Jianing, Wang, Jia, Zheng, Ran, Lu, Weiguo, Grinstein, Sebastian, da Costa, João Guimarães
The Circular Electron Positron Collider (CEPC) has been proposed to enable more thorough and precise measurements of the properties of Higgs, W, and Z bosons, as well as to search for new physics. In response to the stringent performance requirements
Externí odkaz:
http://arxiv.org/abs/2404.03688
Autor:
He, Ye, Li, Xingchen, Xu, Zijun, Qi, Ming, Wang, Congcong, Wang, Chenwei, Lu, Hai, Nie, Xiaojun, Fan, Ruirui, Jing, Hantao, Song, Weiming, Wang, Keqi, Liu, Kai, Liu, Peilian, Li, Hui, Li, Zaiyi, Fu, Chenxi, Zhang, Xiyuan, Kang, Xiaoshen, Li, Zhan, Lu, Weiguo, Xiao, Suyu, Shi, Xin
A high precision beam monitor system based on silicon carbide PIN sensor is designed for China Spallation Neutron Source 1.6 GeV proton beam to monitor the proton beam fluence.The concept design of the beam monitor system is finished together with fr
Externí odkaz:
http://arxiv.org/abs/2403.09244
Diffusion models (DMs) are a type of generative model that has a huge impact on image synthesis and beyond. They achieve state-of-the-art generation results in various generative tasks. A great diversity of conditioning inputs, such as text or boundi
Externí odkaz:
http://arxiv.org/abs/2401.11261
In this work, we present a novel machine learning approach for pricing high-dimensional American options based on the modified Gaussian process regression (GPR). We incorporate deep kernel learning and sparse variational Gaussian processes to address
Externí odkaz:
http://arxiv.org/abs/2311.07211
Autor:
Wu, Tianya, Li, Shuqi, Wang, Wei, Zhou, Jia, Yan, Ziyue, Hu, Yiming, Zhang, Xiaoxu, Liang, Zhijun, Wei, Wei, Zhang, Ying, Wei, Xiaomin, Huang, Xinhui, Zhang, Lei, Qi, Ming, Zeng, Hao, Jia, Xuewei, Hu, Jun, Fu, Jinyu, Zhang, Hongyu, Li, Gang, Wu, Linghui, Dong, Mingyi, Li, Xiaoting, Casanova, Raimon, Zhang, Liang, Dong, Jianing, Wang, Jia, Zheng, Ran, Lu, Weiguo, Grinstein, Sebastian, da Costa, João Guimarães
The proposed Circular Electron Positron Collider (CEPC) imposes new challenges for the vertex detector in terms of pixel size and material budget. A Monolithic Active Pixel Sensor (MAPS) prototype called TaichuPix, based on a column drain readout arc
Externí odkaz:
http://arxiv.org/abs/2311.05932
We propose an Gaussian Mixture Model (GMM) learning algorithm, based on our previous work of GMM expansion idea. The new algorithm brings more robustness and simplicity than classic Expectation Maximization (EM) algorithm. It also improves the accura
Externí odkaz:
http://arxiv.org/abs/2308.09444
MiR-27a inhibits the growth and metastasis of multiple myeloma through regulating Th17/Treg balance.
Autor:
Lu, Weiguo1 (AUTHOR), Huang, Hui2,3 (AUTHOR), Xu, Zhanjie4 (AUTHOR), Xu, Shumin2,3 (AUTHOR), Zhao, Kewei1 (AUTHOR) zkw202420242024@163.com, Xiao, Mingfeng2,3 (AUTHOR) xiaomingfeng2023@163.com
Publikováno v:
PLoS ONE. 10/16/2024, Vol. 19 Issue 10, p1-16. 16p.
For Head and Neck Cancers (HNC) patient management, automatic gross tumor volume (GTV) segmentation and accurate pre-treatment cancer recurrence prediction are of great importance to assist physicians in designing personalized management plans, which
Externí odkaz:
http://arxiv.org/abs/2209.11268
Deep learning (DL) models for medical image segmentation are highly influenced by intensity variations of input images and lack generalization due to primarily utilizing pixels' intensity information for inference. Acquiring sufficient training data
Externí odkaz:
http://arxiv.org/abs/2205.09107