Zobrazeno 1 - 10
of 7 240
pro vyhledávání: '"CHEN, TONG"'
Medical video generation has transformative potential for enhancing surgical understanding and pathology insights through precise and controllable visual representations. However, current models face limitations in controllability and authenticity. T
Externí odkaz:
http://arxiv.org/abs/2412.14018
Autor:
Jiang, Haiyang, Chen, Tong, Zhang, Wentao, Hung, Nguyen Quoc Viet, Yuan, Yuan, Li, Yong, Cui, Lizhen
Urban flow prediction is a classic spatial-temporal forecasting task that estimates the amount of future traffic flow for a given location. Though models represented by Spatial-Temporal Graph Neural Networks (STGNNs) have established themselves as ca
Externí odkaz:
http://arxiv.org/abs/2412.05534
Autor:
Liu, Fang, Ji, Xiao-Bin, Sun, Sheng-Sen, Liu, Huai-Min, Fang, Shuang-Shi, Li, Xiao-Ling, Chen, Tong, Wang, Xin-Nan, Li, Ming-Run, Wang, Liang-Liang, Wu, Ling-Hui, Yuan, Ye, Zhang, Yao, Zhu, Wen-Jing
Using $(10087 \pm 44) \times 10^6$ $J/\psi$ events collected with the BESIII detector in 2009, 2012, 2018 and 2019, the tracking efficiency of charged pions is studied using the decay $J/\psi \rightarrow \pi^+ \pi^- \pi^0$. The systematic uncertainty
Externí odkaz:
http://arxiv.org/abs/2412.00469
Autor:
Li, Jiahan, Chen, Tong, Luo, Shitong, Cheng, Chaoran, Guan, Jiaqi, Guo, Ruihan, Wang, Sheng, Liu, Ge, Peng, Jian, Ma, Jianzhu
Peptides, short chains of amino acids, interact with target proteins, making them a unique class of protein-based therapeutics for treating human diseases. Recently, deep generative models have shown great promise in peptide generation. However, seve
Externí odkaz:
http://arxiv.org/abs/2411.18463
Among various spatio-temporal prediction tasks, epidemic forecasting plays a critical role in public health management. Recent studies have demonstrated the strong potential of spatio-temporal graph neural networks (STGNNs) in extracting heterogeneou
Externí odkaz:
http://arxiv.org/abs/2411.17372
With the increasing computation of training graph neural networks (GNNs) on large-scale graphs, graph condensation (GC) has emerged as a promising solution to synthesize a compact, substitute graph of the large-scale original graph for efficient GNN
Externí odkaz:
http://arxiv.org/abs/2411.17063
Group Point-of-Interest (POI) recommendations aim to predict the next POI that satisfies the diverse preferences of a group of users. This task is more challenging than traditional individual POI recommendations due to complex group decision-making a
Externí odkaz:
http://arxiv.org/abs/2411.13415
Content-based Recommender Systems (CRSs) play a crucial role in shaping user experiences in e-commerce, online advertising, and personalized recommendations. However, due to the vast amount of categorical features, the embedding tables used in CRS mo
Externí odkaz:
http://arxiv.org/abs/2411.13052
The rapid spread of rumors on social media has posed significant challenges to maintaining public trust and information integrity. Since an information cascade process is essentially a propagation tree, recent rumor detection models leverage graph ne
Externí odkaz:
http://arxiv.org/abs/2411.12949
Recommender systems often rely on large embedding tables that map users and items to dense vectors of uniform size, leading to substantial memory consumption and inefficiencies. This is particularly problematic in memory-constrained environments like
Externí odkaz:
http://arxiv.org/abs/2411.12205