J
Jie Tang
Researcher at Tsinghua University
Publications - 599
Citations - 25529
Jie Tang is an academic researcher from Tsinghua University. The author has contributed to research in topics: Computer science & Social network. The author has an hindex of 68, co-authored 466 publications receiving 18934 citations. Previous affiliations of Jie Tang include University of Notre Dame & Renmin University of China.
Papers
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Journal ArticleDOI
Risk factor analysis of omicron patients with mental health problems in the Fangcang shelter hospital based on psychiatric drug intervention during the COVID-19 pandemic in Shanghai, China
Ping Yu,Xiao-Lan Bian,Z. Xie,Xu Wang,Xujing Zhang,Zhidong Gu,Zhi-Tao Yang,F Jing,Weiyu Qiu,Jingxia Lin,Jie Tang,Chen-Ying Huang,Yibo Zhang,Ying Chen,Zongfeng Zhang,Yufang Bi,Han Bing Shang,Erzhen Chen +17 more
TL;DR: Wang et al. as discussed by the authors investigated the risk factors of the infected patients from a new pharmacological perspective based on psychiatric drug consumption rather than questionnaires for the first time, and demonstrated the necessity of potential mental and psychological service development in Fangcang shelters during the COVID-19 pandemic and other public emergency responses.
Posted Content
Does Quantum Interference exist in Twitter
TL;DR: Using twitter data, a mathematical model is proposed to elucidate the spotted quantum phenomena and SIT and CPT fail to interpret the information transfer occurring in Twitter, and quantum interference exists in Twitter.
Posted Content
UFC-BERT: Unifying Multi-Modal Controls for Conditional Image Synthesis
Zhu Zhang,Jianxin Ma,Chang Zhou,Rui Men,Zhikang Li,Ming Ding,Jie Tang,Jingren Zhou,Hongxia Yang +8 more
TL;DR: Zhang et al. as mentioned in this paper proposed a new two-stage architecture, UFC-BERT, to unify any number of multi-modal control signals and the synthesized image are uniformly represented as a sequence of discrete tokens to be processed by Transformer.
Posted Content
GCCAD: Graph Contrastive Coding for Anomaly Detection
Bo Chen,Jing Zhang,Xiaokang Zhang,Yuxiao Dong,Jian Song,Peng Zhang,Kaibo Xu,Evgeny Kharlamov,Jie Tang +8 more
TL;DR: In this article, a graph contrastive coding (GCCAD) model is proposed to contrast abnormal nodes with normal ones in terms of their distances to the global context (e.g., the average of all nodes).
Journal ArticleDOI
Lipid metabolism characterization in gastric cancer identifies signatures to predict prognostic and therapeutic responses
Jiawei Zeng,Honglin Tan,Bin Huang,Qianyu Zhou,Qi Ke,Yan Dai,Jie Tang,Bei Xu,Jiafu Feng,Lin Yu +9 more
TL;DR: Wang et al. as mentioned in this paper applied single-factor Cox regression and random forest to screen signature genes to construct a prognostic model, namely, the lipid metabolism score (LMscore), and deeply explored the predictive value of the LMscore for GC.