Zobrazeno 11 - 20
of 32 009
pro vyhledávání: '"Hong, Yu"'
Current medical artificial intelligence systems are often limited to narrow applications, hindering their widespread adoption in clinical practice. To address this limitation, we propose MedVersa, a generalist learner that enables flexible learning a
Externí odkaz:
http://arxiv.org/abs/2405.07988
In this paper, we have studied the consequences of the $\mu$-$\tau$ reflection symmetry for leptogenesis in the type-I seesaw model with diagonal Dirac neutrino mass matrix. We have first obtained the phenomenologically allowed values of the model pa
Externí odkaz:
http://arxiv.org/abs/2405.02804
Rapidly spinning magnetars are potential candidates for the energy source of supernovae (SNe) and gamma-ray bursts and the most promising sources for continuous gravitational waves (GWs) detected by ground-based GW detectors. Continuous GWs can be ra
Externí odkaz:
http://arxiv.org/abs/2404.18076
Autor:
Li, Hong-Yu, Hu, Jia-Hao
The rotation curve is significant to research on dark matter and the structure of the Milky Way. But it is a great challenge to measure rotation curve accurately, and different ways obtain distinct results. In this work, we use a DIY small radio tele
Externí odkaz:
http://arxiv.org/abs/2404.17893
Autor:
Hu, Jerry Yao-Chieh, Chang, Pei-Hsuan, Luo, Robin, Chen, Hong-Yu, Li, Weijian, Wang, Wei-Po, Liu, Han
We introduce an Outlier-Efficient Modern Hopfield Model (termed $\mathrm{OutEffHop}$) and use it to address the outlier inefficiency problem of {training} gigantic transformer-based models. Our main contribution is a novel associative memory model fa
Externí odkaz:
http://arxiv.org/abs/2404.03828
Automated classification of liver lesions in multi-phase CT and MR scans is of clinical significance but challenging. This study proposes a novel Siamese Dual-Resolution Transformer (SDR-Former) framework, specifically designed for liver lesion class
Externí odkaz:
http://arxiv.org/abs/2402.17246
In this paper we have studied the realizations of the popular TM1 neutrino mixing and neutrino $\mu$-$\tau$ reflection symmetry (which are well motivated from the neutrino oscillation data and lead to interesting phenomenological consequences) in the
Externí odkaz:
http://arxiv.org/abs/2402.14441
Autor:
Wang, Bing-bing, Cheng, Zheyu, Zou, Hong-yu, Ge, Yong, Zhao, Ke-qi, Si, Qiao-rui, Yuan, Shou-qi, Sun, Hong-xiang, Xue, Haoran, Zhang, Baile
The interplay between disorder and topology leads to rich phenomena such as topological Anderson insulator phases, where disorder opens a topological bandgap and thereby enhances transport. With the recent advances in non-Hermitian topological physic
Externí odkaz:
http://arxiv.org/abs/2402.10989
Autor:
Liu, Jiarun, Yang, Hao, Zhou, Hong-Yu, Xi, Yan, Yu, Lequan, Yu, Yizhou, Liang, Yong, Shi, Guangming, Zhang, Shaoting, Zheng, Hairong, Wang, Shanshan
Accurate medical image segmentation demands the integration of multi-scale information, spanning from local features to global dependencies. However, it is challenging for existing methods to model long-range global information, where convolutional n
Externí odkaz:
http://arxiv.org/abs/2402.03302
Parameter-efficient fine-tuning (PEFT) that was initially developed for exploiting pre-trained large language models has recently emerged as an effective approach to perform transfer learning on computer vision tasks. However, the effectiveness of PE
Externí odkaz:
http://arxiv.org/abs/2401.12215