Zobrazeno 1 - 10
of 1 368
pro vyhledávání: '"Liu, Xiaoyi"'
Autor:
Liu, Xiaoyi, Tang, Hao
We introduce DiffFNO, a novel diffusion framework for arbitrary-scale super-resolution strengthened by a Weighted Fourier Neural Operator (WFNO). Mode Re-balancing in WFNO effectively captures critical frequency components, significantly improving th
Externí odkaz:
http://arxiv.org/abs/2411.09911
Autor:
Zeng, Zhichen, Liu, Xiaolong, Hang, Mengyue, Liu, Xiaoyi, Zhou, Qinghai, Yang, Chaofei, Liu, Yiqun, Ruan, Yichen, Chen, Laming, Chen, Yuxin, Hao, Yujia, Xu, Jiaqi, Nie, Jade, Liu, Xi, Zhang, Buyun, Wen, Wei, Yuan, Siyang, Wang, Kai, Chen, Wen-Yen, Han, Yiping, Li, Huayu, Yang, Chunzhi, Long, Bo, Yu, Philip S., Tong, Hanghang, Yang, Jiyan
Click-through rate (CTR) prediction, which predicts the probability of a user clicking an ad, is a fundamental task in recommender systems. The emergence of heterogeneous information, such as user profile and behavior sequences, depicts user interest
Externí odkaz:
http://arxiv.org/abs/2411.09852
Autor:
Liu, Xiaoyi, Du, Ruina, Tan, Lianghao, Xu, Junran, Chen, Chen, Jiang, Huangqi, Aldwais, Saleh
Ensuring safety on construction sites is critical, with helmets playing a key role in reducing injuries. Traditional safety checks are labor-intensive and often insufficient. This study presents a computer vision-based solution using YOLO for real-ti
Externí odkaz:
http://arxiv.org/abs/2410.20699
Gravitational R\'enyi computations have traditionally been described in the language of Euclidean path integrals. In the semiclassical limit, such calculations are governed by Euclidean (or, more generally, complex) saddle-point geometries. We emphas
Externí odkaz:
http://arxiv.org/abs/2409.17428
Autor:
Liu, Xiaoyi, Yang, Hongpeng, Ai, Chengwei, Dong, Ruihan, Ding, Yijie, Yuan, Qianqian, Tang, Jijun, Guo, Fei
Incomplete knowledge of metabolic processes hinders the accuracy of GEnome-scale Metabolic models (GEMs), which in turn impedes advancements in systems biology and metabolic engineering. Existing gap-filling methods typically rely on phenotypic data
Externí odkaz:
http://arxiv.org/abs/2409.13259
In e-commerce websites, web mining web page recommendation technology has been widely used. However, recommendation solutions often cannot meet the actual application needs of online shopping users. To address this problem, this paper proposes an e-c
Externí odkaz:
http://arxiv.org/abs/2409.07033
Skin lesions are an increasingly significant medical concern, varying widely in severity from benign to cancerous. Accurate diagnosis is essential for ensuring timely and appropriate treatment. This study examines the implementation of deep learning
Externí odkaz:
http://arxiv.org/abs/2409.04381
Many people die from lung-related diseases every year. X-ray is an effective way to test if one is diagnosed with a lung-related disease or not. This study concentrates on categorizing three distinct types of lung X-rays: those depicting healthy lung
Externí odkaz:
http://arxiv.org/abs/2408.13180
A long-standing challenge in end-user programming (EUP) is to trade off between natural user expression and the complexity of programming tasks. As large language models (LLMs) are empowered to handle semantic inference and natural language understan
Externí odkaz:
http://arxiv.org/abs/2408.12687
Autor:
Ying, Rui, Hu, Mengting, Wu, Jianfeng, Xie, Yalan, Liu, Xiaoyi, Wang, Zhunheng, Jiang, Ming, Gao, Hang, Zhang, Linlin, Cheng, Renhong
Temporal knowledge graph completion aims to infer the missing facts in temporal knowledge graphs. Current approaches usually embed factual knowledge into continuous vector space and apply geometric operations to learn potential patterns in temporal k
Externí odkaz:
http://arxiv.org/abs/2408.06603