Zobrazeno 1 - 10
of 198
pro vyhledávání: '"Hesen, P."'
Autor:
Chen, Daoyuan, Huang, Yilun, Ma, Zhijian, Chen, Hesen, Pan, Xuchen, Ge, Ce, Gao, Dawei, Xie, Yuexiang, Liu, Zhaoyang, Gao, Jinyang, Li, Yaliang, Ding, Bolin, Zhou, Jingren
The immense evolution in Large Language Models (LLMs) has underscored the importance of massive, heterogeneous, and high-quality data. A data recipe is a mixture of data from different sources for training LLMs, which plays a vital role in LLMs' perf
Externí odkaz:
http://arxiv.org/abs/2309.02033
Autor:
Luijken, K., Lohmann, A., Alter, U., Gonzalez, J. Claramunt, Clouth, F. J., Fossum, J. L., Hesen, L., Huizing, A. H. J., Ketelaar, J., Montoya, A. K., Nab, L., Nijman, R. C. C., de Vries, B. B. L. Penning, Tibbe, T. D., Wang, Y. A., Groenwold, R. H. H.
Results of simulation studies evaluating the performance of statistical methods are often considered actionable and thus can have a major impact on the way empirical research is implemented. However, so far there is limited evidence about the reprodu
Externí odkaz:
http://arxiv.org/abs/2307.02052
Publikováno v:
Mathematical and Computer Modelling of Dynamical Systems, Vol 30, Iss 1, Pp 736-757 (2024)
In order to make the constructed investment portfolio model better adapt to the actual securities market, this paper incorporates the multifractal correlations into the portfolio model of multi-risk assets optimization. On the basis of using variable
Externí odkaz:
https://doaj.org/article/b84b04397cea49818da47dd15d426480
The wide application of pre-trained models is driving the trend of once-for-all training in one-shot neural architecture search (NAS). However, training within a huge sample space damages the performance of individual subnets and requires much comput
Externí odkaz:
http://arxiv.org/abs/2304.14636
Publikováno v:
Drugs in R&D, Vol 24, Iss 2, Pp 317-329 (2024)
Abstract Background and Objective Atorvastatin is a drug widely used to prevent cardiovascular and cerebrovascular diseases. Current observational studies suggest that atorvastatin may be associated with cognitive dysfunction (especially memory loss)
Externí odkaz:
https://doaj.org/article/7505c2376300428382669f6051736168
Autor:
Hesen Xiong, Zongliang Zhang, Jiaxin Dai, Pei Zhao, Kai He, Jie Gao, Dr. Qiang Wu, Dr. Baofeng Wang
Publikováno v:
ChemElectroChem, Vol 11, Iss 21, Pp n/a-n/a (2024)
Abstract The practical application of LiMn1−xFexPO4 as a cathode material is hindered considerably by its poor electronic conductivity and slow lithium‐ion diffusion. In the present study, a uniform nitrogen‐doped carbon coating on LiMn0.7Fe0.3
Externí odkaz:
https://doaj.org/article/b3569ca350984110845bdfca64a183d3
Autor:
Saumey Jain, Dimitrios Voulgaris, Surangrat Thongkorn, Rick Hesen, Alice Hägg, Mohsen Moslem, Anna Falk, Anna Herland
Publikováno v:
Advanced Science, Vol 11, Iss 25, Pp n/a-n/a (2024)
Abstract The clinical translation of induced pluripotent stem cells (iPSCs) holds great potential for personalized therapeutics. However, one of the main obstacles is that the current workflow to generate iPSCs is expensive, time‐consuming, and req
Externí odkaz:
https://doaj.org/article/0970680dbdd14e2a9321702f426f885c
Publikováno v:
Frontiers in Pharmacology, Vol 15 (2024)
Background:Atorvastatin is a commonly prescribed medication for the prevention of cardiovascular diseases. Recent observational studies have suggested a potential association between atorvastatin use and the occurrence of Erectile Dysfunction (ED). I
Externí odkaz:
https://doaj.org/article/bb8dc2a144e5401ba726ad24e5dc4f94
Data augmentation is a commonly used approach to improving the generalization of deep learning models. Recent works show that learned data augmentation policies can achieve better generalization than hand-crafted ones. However, most of these works us
Externí odkaz:
http://arxiv.org/abs/2107.05384
Autor:
Lin, Ming, Wang, Pichao, Sun, Zhenhong, Chen, Hesen, Sun, Xiuyu, Qian, Qi, Li, Hao, Jin, Rong
Accuracy predictor is a key component in Neural Architecture Search (NAS) for ranking architectures. Building a high-quality accuracy predictor usually costs enormous computation. To address this issue, instead of using an accuracy predictor, we prop
Externí odkaz:
http://arxiv.org/abs/2102.01063