Zobrazeno 1 - 10
of 241
pro vyhledávání: '"Wang, Tianren"'
In recent years, researchers have been exploring the applications of noisy intermediate-scale quantum (NISQ) computation in various fields. One important area in which quantum computation can outperform classical computers is the ground state problem
Externí odkaz:
http://arxiv.org/abs/2306.08885
Autor:
Wang, Tianren1, Li, Yunhao2, Yu, Chenao1, Lv, Xinru3, Weng, Yuxuan3, Zhang, Zhixuan4, Xu, Haozhen3, Liang, Runjia3, Wang, Mengyue3, Weng, Zhenzhen3, Zhang, Cheng3, Lv, Yi5 luyi169@126.com, Zhang, Yong1 zhangyongyang05@163.com
Publikováno v:
Scientific Reports. 9/2/2024, Vol. 14 Issue 1, p1-12. 12p.
The continual appearance of new objects in the visual world poses considerable challenges for current deep learning methods in real-world deployments. The challenge of new task learning is often exacerbated by the scarcity of data for the new categor
Externí odkaz:
http://arxiv.org/abs/2208.00147
Autor:
Wang, Tianren, Gao, Jingru, Xu, Jinghan, Hong, Yuxiang, Du, Ronghuan, Zheng, Xian, Wang, Peng
Publikováno v:
In International Journal of Biological Macromolecules October 2024 277 Part 4
One-step hydrothermal preparation of pine-dendritic La-doped CdS nanomaterials for n-butanol sensing
Autor:
Yue, Chen, Zhou, Kaiwen, Wang, Tianren, Liu, Zhenyue, Yang, Zhiguo, Mu, Yang, Zhang, Zhenkai, Wang, Feifei, Dastan, Davoud, Yin, Xi-Tao, Tan, Guanglei, Ma, Xiaoguang
Publikováno v:
In Ceramics International 1 October 2024 50(19) Part A:35575-35582
Autor:
Yang, Zhiguo, Chen, Xingtai, Chen, Qiuying, Qu, Jiayi, Guo, Yujun, Zhou, Kaiwen, Wang, Tianren, Dastan, Davoud, Wang, Xiaoning, Wang, Feifei, Tan, Xiaoming, Yin, Xi-Tao, Ma, Xiaoguang
Publikováno v:
In Sensors and Actuators: B. Chemical 1 February 2025 424
With the excellent disentanglement properties of state-of-the-art generative models, image editing has been the dominant approach to control the attributes of synthesised face images. However, these edited results often suffer from artifacts or incor
Externí odkaz:
http://arxiv.org/abs/2109.03492
To accommodate rapid changes in the real world, the cognition system of humans is capable of continually learning concepts. On the contrary, conventional deep learning models lack this capability of preserving previously learned knowledge. When a neu
Externí odkaz:
http://arxiv.org/abs/2108.05627
Autor:
Han, Jie, Wen, Xin, Wang, Hongchao, Wang, Tianren, Sun, Yuzhen, Ricardez-Sandoval, Luis, Bai, Guoyi
Publikováno v:
In Molecular Catalysis 15 April 2024 559
Text-to-Face (TTF) synthesis is a challenging task with great potential for diverse computer vision applications. Compared to Text-to-Image (TTI) synthesis tasks, the textual description of faces can be much more complicated and detailed due to the v
Externí odkaz:
http://arxiv.org/abs/2006.07606