Zobrazeno 1 - 10
of 381
pro vyhledávání: '"Yang Zhixian"'
Autor:
Liu Chao, Wang Yun, Dao Yuyang, Wang Shuting, Hou Fei, Yang Zhixian, Liu Pengjie, Lv Juan, Lv Ling, Li Gaofeng, Zhou Youjun, Deng Zhiyong
Publikováno v:
Acta Biochimica et Biophysica Sinica, Vol 54, Pp 99-112 (2021)
Centromere protein M (CENPM) is essential for chromosome separation during mitosis. However, its roles in lung adenocarcinoma (LUAD) progression and metastasis remain unknown. In this study, we aimed to explore the effects of CENPM on LUAD progressio
Externí odkaz:
https://doaj.org/article/871074bf7cc44f6b9afd78c024c3ded2
Publikováno v:
精准医学杂志, Vol 39, Iss 3, Pp 218-221 (2024)
Objective To investigate the clinical and electroencephalographic (EEG) features of children with eating-induced reflex epilepsy. Methods A retrospective analysis was performed for the clinical features, EEG findings, treatment, and prognosis of thre
Externí odkaz:
https://doaj.org/article/0a2c8d6bfdac41b09d3c8d721bc99e6a
One of the major problems with text simplification is the lack of high-quality data. The sources of simplification datasets are limited to Wikipedia and Newsela, restricting further development of this field. In this paper, we analyzed the similarity
Externí odkaz:
http://arxiv.org/abs/2302.07124
k-nearest-neighbor machine translation (NN-MT), proposed by Khandelwal et al. (2021), has achieved many state-of-the-art results in machine translation tasks. Although effective, NN-MT requires conducting NN searches through the large datastore for e
Externí odkaz:
http://arxiv.org/abs/2205.00479
Autor:
Yang, Zhixian, Wan, Xiaojun
Various models have been proposed to incorporate knowledge of syntactic structures into neural language models. However, previous works have relied heavily on elaborate components for a specific language model, usually recurrent neural network (RNN),
Externí odkaz:
http://arxiv.org/abs/2203.10256
Publikováno v:
In Journal of Building Engineering 1 November 2024 96
Publikováno v:
In Clinical Neurophysiology August 2024 164:24-29
Neural text generation models are likely to suffer from the low-diversity problem. Various decoding strategies and training-based methods have been proposed to promote diversity only by exploiting contextual features, but rarely do they consider inco
Externí odkaz:
http://arxiv.org/abs/2105.03641
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