Zobrazeno 1 - 10
of 183
pro vyhledávání: '"Liu, Hanzhou"'
Sequential recommender systems aims to predict the users' next interaction through user behavior modeling with various operators like RNNs and attentions. However, existing models generally fail to achieve the three golden principles for sequential r
Externí odkaz:
http://arxiv.org/abs/2406.12580
Although prior state-of-the-art (SOTA) deblurring networks achieve high metric scores on synthetic datasets, there are two challenges which prevent them from perceptual image deblurring. First, a deblurring model overtrained on synthetic datasets may
Externí odkaz:
http://arxiv.org/abs/2403.13163
Sequential recommendation aims to estimate the dynamic user preferences and sequential dependencies among historical user behaviors. Although Transformer-based models have proven to be effective for sequential recommendation, they suffer from the inf
Externí odkaz:
http://arxiv.org/abs/2403.03900
Autor:
Chen, Mingjing, Liu, Hanzhou, Liu, Haidong, Zhong, Lei, Deng, Jian, Zuo, Qianlong, Wu, Junchen, Chen, Deqi
Publikováno v:
In International Journal of Heat and Mass Transfer 15 August 2024 228
Publikováno v:
In Progress in Nuclear Energy August 2024 173
Autor:
Feng, Peng, Liu, Hanzhou, Chen, Mingjing, Ding, Shuhua, Wu, Dan, Deng, Jian, Liu, Haidong, Chen, Deqi
Publikováno v:
In Progress in Nuclear Energy May 2024 170
Autor:
Liu, Haidong, Dong, Kejian, Yan, Peigang, Zhao, Jiyun, Hibiki, Takashi, Qin, Jiang, Liu, Hanzhou, Chen, Deqi
Publikováno v:
In International Journal of Thermal Sciences April 2024 198
Publikováno v:
In Annals of Nuclear Energy April 2024 198
Publikováno v:
In Applied Thermal Engineering 5 January 2024 236 Part A
Publikováno v:
In International Journal of Thermal Sciences January 2024 195