Zobrazeno 1 - 10
of 545
pro vyhledávání: '"ZHENG Zeyu"'
Publikováno v:
Acta Biochimica et Biophysica Sinica, Vol 54, Pp 1068-1079 (2022)
Osteoporosis deteriorates bone mass and biomechanical strength and is life-threatening to the elderly. In this study, we show that methyl 3,4-dihydroxybenzoate (MDHB), an antioxidant small-molecule compound extracted from natural plants, inhibits rec
Externí odkaz:
https://doaj.org/article/d20083bfa1bd45e4b96856ab64b65e62
Autor:
Zheng Zeyu, Miao Yu, Yao Jiyuan, Chen Jiamei, Wen Jialin, Chen Xiaodan, Lu Yanxin, Jiang Xiaofang, Shui Lingling
Publikováno v:
Nanophotonics, Vol 11, Iss 16, Pp 3641-3651 (2022)
Hierarchical and periodic nanostructures of dielectrics or metals are highly demanded for wide applications in optical, electrical, biological, and quantum devices. In this work, programmable plasmonic–photonic hierarchical nanostructures are fabri
Externí odkaz:
https://doaj.org/article/85bf9af39a6142669bbb6a6b98d0901a
We propose a class of structured diffusion models, in which the prior distribution is chosen as a mixture of Gaussians, rather than a standard Gaussian distribution. The specific mixed Gaussian distribution, as prior, can be chosen to incorporate cer
Externí odkaz:
http://arxiv.org/abs/2410.19149
The problem of symbolic music generation presents unique challenges due to the combination of limited data availability and the need for high precision in note pitch. To overcome these difficulties, we introduce Fine-grained Textural Guidance (FTG) w
Externí odkaz:
http://arxiv.org/abs/2410.08435
Autor:
Lyle, Clare, Zheng, Zeyu, Khetarpal, Khimya, Martens, James, van Hasselt, Hado, Pascanu, Razvan, Dabney, Will
Normalization layers have recently experienced a renaissance in the deep reinforcement learning and continual learning literature, with several works highlighting diverse benefits such as improving loss landscape conditioning and combatting overestim
Externí odkaz:
http://arxiv.org/abs/2407.01800
Autor:
Zhang, Haoting, Zhan, Donglin, Lin, Yunduan, He, Jinghai, Zhu, Qing, Shen, Zuo-Jun Max, Zheng, Zeyu
In healthcare applications, there is a growing need to develop machine learning models that use data from a single source, such as that from a wrist wearable device, to monitor physical activities, assess health risks, and provide immediate health re
Externí odkaz:
http://arxiv.org/abs/2405.16395
Autor:
Tang, Yunhao, Guo, Daniel Zhaohan, Zheng, Zeyu, Calandriello, Daniele, Cao, Yuan, Tarassov, Eugene, Munos, Rémi, Pires, Bernardo Ávila, Valko, Michal, Cheng, Yong, Dabney, Will
Reinforcement learning from human feedback (RLHF) is the canonical framework for large language model alignment. However, rising popularity in offline alignment algorithms challenge the need for on-policy sampling in RLHF. Within the context of rewar
Externí odkaz:
http://arxiv.org/abs/2405.08448
Pre-trained large language models (LLM) have emerged as a powerful tool for simulating various scenarios and generating output given specific instructions and multimodal input. In this work, we analyze the specific use of LLM to enhance a classical s
Externí odkaz:
http://arxiv.org/abs/2405.05445
Drug discovery is a complex process that involves sequentially screening and examining a vast array of molecules to identify those with the target properties. This process, also referred to as sequential experimentation, faces challenges due to the v
Externí odkaz:
http://arxiv.org/abs/2405.03942
We provide a preliminary study on utilizing GPU (Graphics Processing Unit) to accelerate computation for three simulation optimization tasks with either first-order or second-order algorithms. Compared to the implementation using only CPU (Central Pr
Externí odkaz:
http://arxiv.org/abs/2404.11631