Zobrazeno 1 - 10
of 15 927
pro vyhledávání: '"Yao, Yao"'
Autor:
Chen, Zeyu, Wang, Enci, Zou, Hu, Zou, Siwei, Gao, Yang, Wang, Huiyuan, Yu, Haoran, Jia, Cheng, Li, Haixin, Ma, Chengyu, Yao, Yao, Ding, Weiyu, Zhu, Runyu
Understanding the circumgalactic medium (CGM) distribution of galaxies is the key to revealing the dynamical exchange of materials between galaxies and their surroundings. In this work, we use DESI EDR dataset to investigate the cool CGM of galaxies
Externí odkaz:
http://arxiv.org/abs/2411.08485
Autor:
Jia, Cheng, Wang, Enci, Wang, Huiyuan, Li, Hui, Yao, Yao, Song, Jie, Zhang, Hongxin, Rong, Yu, Chen, Yangyao, Yu, Haoran, Chen, Zeyu, Li, Haixin, Ma, Chengyu, Kong, Xu
We investigate size variation with rest-frame wavelength for star-forming galaxies based on the second JWST Advanced Deep Extragalactic Survey data release. Star-forming galaxies are typically smaller at longer wavelength from UV-to-NIR at $z<3.5$, e
Externí odkaz:
http://arxiv.org/abs/2411.07458
Autor:
Cui, Jiahao, Li, Hui, Yao, Yao, Zhu, Hao, Shang, Hanlin, Cheng, Kaihui, Zhou, Hang, Zhu, Siyu, Wang, Jingdong
Recent advances in latent diffusion-based generative models for portrait image animation, such as Hallo, have achieved impressive results in short-duration video synthesis. In this paper, we present updates to Hallo, introducing several design enhanc
Externí odkaz:
http://arxiv.org/abs/2410.07718
In the real world, a learning-enabled system usually undergoes multiple cycles of model development to enhance the system's ability to handle difficult or emerging tasks. This continual model development process raises a significant issue that the mo
Externí odkaz:
http://arxiv.org/abs/2410.03955
Autor:
Zhuang, Yiyu, He, Yuxiao, Zhang, Jiawei, Wang, Yanwen, Zhu, Jiahe, Yao, Yao, Zhu, Siyu, Cao, Xun, Zhu, Hao
Creating 3D head avatars is a significant yet challenging task for many applicated scenarios. Previous studies have set out to learn 3D human head generative models using massive 2D image data. Although these models are highly generalizable for human
Externí odkaz:
http://arxiv.org/abs/2410.01226
Large language models (LLMs) have rapidly advanced and demonstrated impressive capabilities. In-Context Learning (ICL) and Parameter-Efficient Fine-Tuning (PEFT) are currently two mainstream methods for augmenting LLMs to downstream tasks. ICL typica
Externí odkaz:
http://arxiv.org/abs/2409.20181
For the 2D incompressible Euler equations, we establish global-in-time ($t \in \mathbb{R}$) stability of vortex quadrupoles satisfying odd symmetry with respect to both axes. Specifically, if the vorticity restricted to a quadrant is signed, sufficie
Externí odkaz:
http://arxiv.org/abs/2409.19822
We report the evidence of a hidden black hole (BH) in a low-mass galaxy, MaNGA 9885-9102, and provide a new method to identify active BH in low mass galaxies. This galaxy is originally selected from the MaNGA survey with distinctive bipolar H$\alpha$
Externí odkaz:
http://arxiv.org/abs/2408.13841
Autor:
Cheng, Kaihui, Liu, Ce, Su, Qingkun, Wang, Jun, Zhang, Liwei, Tang, Yining, Yao, Yao, Zhu, Siyu, Qi, Yuan
Protein structure prediction is pivotal for understanding the structure-function relationship of proteins, advancing biological research, and facilitating pharmaceutical development and experimental design. While deep learning methods and the expande
Externí odkaz:
http://arxiv.org/abs/2408.12419
Small satellites such as CubeSats pose demanding requirements on the weight, size, and multifunctionality of their structures due to extreme constraints on the payload mass and volume. To address this challenge, we introduce a concept of multifunctio
Externí odkaz:
http://arxiv.org/abs/2408.08491