Zobrazeno 1 - 10
of 5 946
pro vyhledávání: '"Bao, Yu"'
Publikováno v:
Optics Express 32, 24629 (2024)
Quantum conference key agreement (QCKA) enables the unconditional secure distribution of conference keys among multiple participants. Due to challenges in high-fidelity preparation and long-distance distribution of multi-photon entanglement, entangle
Externí odkaz:
http://arxiv.org/abs/2406.17267
Recently, Large Language Models (LLMs) have demonstrated outstanding performance across a wide range of downstream language tasks. Temperature sampling is a commonly used decoding strategy for LLMs' generation process. However, a fixed temperature pa
Externí odkaz:
http://arxiv.org/abs/2403.14541
Recently, 3D generative models have shown promising performances in structure-based drug design by learning to generate ligands given target binding sites. However, only modeling the target-ligand distribution can hardly fulfill one of the main goals
Externí odkaz:
http://arxiv.org/abs/2403.13829
Autor:
Guan, Jiaqi, Zhou, Xiangxin, Yang, Yuwei, Bao, Yu, Peng, Jian, Ma, Jianzhu, Liu, Qiang, Wang, Liang, Gu, Quanquan
Designing 3D ligands within a target binding site is a fundamental task in drug discovery. Existing structured-based drug design methods treat all ligand atoms equally, which ignores different roles of atoms in the ligand for drug design and can be l
Externí odkaz:
http://arxiv.org/abs/2403.07902
Autor:
Huang, Zhilin, Yang, Ling, Zhang, Zaixi, Zhou, Xiangxin, Bao, Yu, Zheng, Xiawu, Yang, Yuwei, Wang, Yu, Yang, Wenming
Structure-based drug design (SBDD) aims to generate 3D ligand molecules that bind to specific protein targets. Existing 3D deep generative models including diffusion models have shown great promise for SBDD. However, it is complex to capture the esse
Externí odkaz:
http://arxiv.org/abs/2402.18583
The recent surge of generative AI has been fueled by the generative power of diffusion probabilistic models and the scalable capabilities of large language models. Despite their potential, it remains elusive whether diffusion language models can solv
Externí odkaz:
http://arxiv.org/abs/2308.12219
Benefiting from the sequence-level knowledge distillation, the Non-Autoregressive Transformer (NAT) achieves great success in neural machine translation tasks. However, existing knowledge distillation has side effects, such as propagating errors from
Externí odkaz:
http://arxiv.org/abs/2303.17910
While diffusion models have achieved great success in generating continuous signals such as images and audio, it remains elusive for diffusion models in learning discrete sequence data like natural languages. Although recent advances circumvent this
Externí odkaz:
http://arxiv.org/abs/2302.10025
Autor:
Bao Yu, Chen Haoran
Publikováno v:
Redai dili, Vol 44, Iss 4, Pp 724-732 (2024)
At the height of the national independence movements in Asia, Africa, and Latin America in the first half of the 20th century, postcolonial thought began to emerge in Brazil, reconstructing the self-other relation between Brazil and the West. The ima
Externí odkaz:
https://doaj.org/article/71202485b331425da05ab9c5ec679728
Autor:
Yi-fan Li, Yang Yang, Xiang-long Kong, Wan-mei Song, Ya-meng Li, Ying-Ying Li, Wei-wei Fang, Jie-yu Yang, Dan Men, Chun-Bao Yu, Guo-ru Yang, Wen-ge Han, Wen-yu Liu, Kun Yan, Huai-chen Li, Yao Liu
Publikováno v:
International Journal of Infectious Diseases, Vol 140, Iss , Pp 124-131 (2024)
Objectives: This study aimed to describe the lineage-specific transmissibility and epidemiological migration of Mycobacterium tuberculosis in China. Methods: We curated a large set of whole-genome sequences from 3204 M. tuberculosis isolates, includi
Externí odkaz:
https://doaj.org/article/3156effc5c2d4ae585a2297f3785003b