Zobrazeno 1 - 10
of 221
pro vyhledávání: '"Zhao Yunxiang"'
Autor:
Yuan Renqiang, Luo Xiaorong, Liang Ziyun, Cai Shufang, Zhao Yunxiang, Zhu Qi, Li Enru, Liu Xiaohong, Mo Delin, Chen Yaosheng
Publikováno v:
Acta Biochimica et Biophysica Sinica, Vol 56, Pp 1065-1071 (2024)
Ubiquitin-conjugation enzyme E2C (UBE2C) is a crucial component of the ubiquitin-proteasome system that is involved in numerous cancers. In this study, we find that UBE2C expression is significantly increased in mouse embryos, a critical stage during
Externí odkaz:
https://doaj.org/article/454cf307d1824cc294eedd973d9eec72
Self-training emerges as an important research line on domain adaptation. By taking the model's prediction as the pseudo labels of the unlabeled data, self-training bootstraps the model with pseudo instances in the target domain. However, the predict
Externí odkaz:
http://arxiv.org/abs/2308.02753
Text classification is a fundamental task for natural language processing, and adapting text classification models across domains has broad applications. Self-training generates pseudo-examples from the model's predictions and iteratively trains on t
Externí odkaz:
http://arxiv.org/abs/2308.02746
Publikováno v:
E3S Web of Conferences, Vol 131, p 01053 (2019)
Selection of well and reservoir is an important step in the process of stimulation and transformation of oil fields. Good measures can effectively save the cost in the process of oil field development and greatly increase the production of oil fields
Externí odkaz:
https://doaj.org/article/7d363414473341d399702247bfd534d8
Detecting beneficial feature interactions is essential in recommender systems, and existing approaches achieve this by examining all the possible feature interactions. However, the cost of examining all the possible higher-order feature interactions
Externí odkaz:
http://arxiv.org/abs/2206.13764
Publikováno v:
In Heliyon 15 June 2024 10(11)
Graph pooling that summaries the information in a large graph into a compact form is essential in hierarchical graph representation learning. Existing graph pooling methods either suffer from high computational complexity or cannot capture the global
Externí odkaz:
http://arxiv.org/abs/2105.01275
Graph structural information such as topologies or connectivities provides valuable guidance for graph convolutional networks (GCNs) to learn nodes' representations. Existing GCN models that capture nodes' structural information weight in- and out-ne
Externí odkaz:
http://arxiv.org/abs/2104.14060
Hexagonal CNN models have shown superior performance in applications such as IACT data analysis and aerial scene classification due to their better rotation symmetry and reduced anisotropy. In order to realize hexagonal processing, existing studies m
Externí odkaz:
http://arxiv.org/abs/2101.10897
Publikováno v:
In Theriogenology February 2024 215:351-360