Zobrazeno 1 - 10
of 212
pro vyhledávání: '"Xu, Yanbo"'
Autor:
Chaves, Juan Manuel Zambrano, Huang, Shih-Cheng, Xu, Yanbo, Xu, Hanwen, Usuyama, Naoto, Zhang, Sheng, Wang, Fei, Xie, Yujia, Khademi, Mahmoud, Yang, Ziyi, Awadalla, Hany, Gong, Julia, Hu, Houdong, Yang, Jianwei, Li, Chunyuan, Gao, Jianfeng, Gu, Yu, Wong, Cliff, Wei, Mu, Naumann, Tristan, Chen, Muhao, Lungren, Matthew P., Chaudhari, Akshay, Yeung-Levy, Serena, Langlotz, Curtis P., Wang, Sheng, Poon, Hoifung
The scaling laws and extraordinary performance of large foundation models motivate the development and utilization of such models in biomedicine. However, despite early promising results on some biomedical benchmarks, there are still major challenges
Externí odkaz:
http://arxiv.org/abs/2403.08002
Transformer Hawkes process models have shown to be successful in modeling event sequence data. However, most of the existing training methods rely on maximizing the likelihood of event sequences, which involves calculating some intractable integral.
Externí odkaz:
http://arxiv.org/abs/2310.16336
FaceDNeRF: Semantics-Driven Face Reconstruction, Prompt Editing and Relighting with Diffusion Models
The ability to create high-quality 3D faces from a single image has become increasingly important with wide applications in video conferencing, AR/VR, and advanced video editing in movie industries. In this paper, we propose Face Diffusion NeRF (Face
Externí odkaz:
http://arxiv.org/abs/2306.00783
Autor:
Zhang, Sheng, Xu, Yanbo, Usuyama, Naoto, Xu, Hanwen, Bagga, Jaspreet, Tinn, Robert, Preston, Sam, Rao, Rajesh, Wei, Mu, Valluri, Naveen, Wong, Cliff, Tupini, Andrea, Wang, Yu, Mazzola, Matt, Shukla, Swadheen, Liden, Lars, Gao, Jianfeng, Lungren, Matthew P., Naumann, Tristan, Wang, Sheng, Poon, Hoifung
Biomedical data is inherently multimodal, comprising physical measurements and natural language narratives. A generalist biomedical AI model needs to simultaneously process different modalities of data, including text and images. Therefore, training
Externí odkaz:
http://arxiv.org/abs/2303.00915
Autor:
Xu, Yanbo, Khare, Alind, Matlin, Glenn, Ramadoss, Monish, Kamaleswaran, Rishikesan, Zhang, Chao, Tumanov, Alexey
Machine Learning (ML) research has focused on maximizing the accuracy of predictive tasks. ML models, however, are increasingly more complex, resource intensive, and costlier to deploy in resource-constrained environments. These issues are exacerbate
Externí odkaz:
http://arxiv.org/abs/2210.15056
Publikováno v:
Zhongguo shipin weisheng zazhi, Vol 36, Iss 3, Pp 309-313 (2024)
ObjectiveTo understand the public’s cognition， trust and negative emotions towards food safety supervision and sampling inspection. Analyze the relationship between the three. To provide scientific basis for improving the ability of food safety s
Externí odkaz:
https://doaj.org/article/ee95175b2bda4c5e9e051a7c1ec8cc71
Autor:
Xu, Yanbo, Yin, Yueqin, Jiang, Liming, Wu, Qianyi, Zheng, Chengyao, Loy, Chen Change, Dai, Bo, Wu, Wayne
Recent advances like StyleGAN have promoted the growth of controllable facial editing. To address its core challenge of attribute decoupling in a single latent space, attempts have been made to adopt dual-space GAN for better disentanglement of style
Externí odkaz:
http://arxiv.org/abs/2203.17266
Autor:
Zhao, Hongtao, Zhang, Yu, Xu, Yanbo, Shao, Yongjun, Chen, Xiaoyan, Hao, Jiayao, Zhao, Lianjie, Shen, Hongjie, Wang, Xu
Publikováno v:
In Ore Geology Reviews May 2024 168
Investigation on triboelectrification behavior of surface nanocrystallization of medium carbon steel
Autor:
Li, Qingtao, Li, Guobin, Xing, Pengfei, Zhang, Hongpeng, Zhou, Yun, Zhang, Lu, Xu, Yanbo, Zheng, Xieqing, Jiang, Yunlong, Zhao, Yao
Publikováno v:
In Tribology International April 2024 192
Publikováno v:
In Clinical Breast Cancer January 2024 24(1):7-16