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pro vyhledávání: '"Chen, Luonan"'
Causality inference is prone to spurious causal interactions, due to the substantial confounders in a complex system. While many existing methods based on the statistical methods or dynamical methods attempt to address misidentification challenges, t
Externí odkaz:
http://arxiv.org/abs/2408.05584
Inferring causal links or subgraphs corresponding to a specific phenotype or label based solely on measured data is an important yet challenging task, which is also different from inferring causal nodes. While Graph Neural Network (GNN) Explainers ha
Externí odkaz:
http://arxiv.org/abs/2407.19376
Detecting and quantifying causality is a focal topic in the fields of science, engineering, and interdisciplinary studies. However, causal studies on non-intervention systems attract much attention but remain extremely challenging. To address this ch
Externí odkaz:
http://arxiv.org/abs/2407.01621
Autor:
Jia, Junbo, Chen, Luonan
The Waddington landscape serves as a metaphor illustrating the developmental process of cells, likening it to a small ball rolling down various trajectories into valleys. Constructing an epigenetic landscape of this nature aids in visualizing and gai
Externí odkaz:
http://arxiv.org/abs/2311.10403
Making an accurate prediction of an unknown system only from a short-term time series is difficult due to the lack of sufficient information, especially in a multi-step-ahead manner. However, a high-dimensional short-term time series contains rich dy
Externí odkaz:
http://arxiv.org/abs/2204.12085
Making predictions in a robust way is a difficult task only based on the observed data of a nonlinear system. In this work, a neural network computing framework, the spatiotemporal information conversion machine (STICM), was developed to efficiently
Externí odkaz:
http://arxiv.org/abs/2107.01353
Autor:
Deng, Yulan, Xia, Liang, Zhang, Jian, Deng, Senyi, Wang, Mengyao, Wei, Shiyou, Li, Kaixiu, Lai, Hongjin, Yang, Yunhao, Bai, Yuquan, Liu, Yongcheng, Luo, Lanzhi, Yang, Zhenyu, Chen, Yaohui, Kang, Ran, Gan, Fanyi, Pu, Qiang, Mei, Jiandong, Ma, Lin, Lin, Feng, Guo, Chenglin, Liao, Hu, Zhu, Yunke, Liu, Zheng, Liu, Chengwu, Hu, Yang, Yuan, Yong, Zha, Zhengyu, Yuan, Gang, Zhang, Gao, Chen, Luonan, Cheng, Qing, Shen, Shensi, Liu, Lunxu
Publikováno v:
In Cell Reports Medicine 16 April 2024 5(4)
Autor:
Tong, Xinyuan, Patel, Ayushi S., Kim, Eejung, Li, Hongjun, Chen, Yueqing, Li, Shuai, Liu, Shengwu, Dilly, Julien, Kapner, Kevin S., Zhang, Ningxia, Xue, Yun, Hover, Laura, Mukhopadhyay, Suman, Sherman, Fiona, Myndzar, Khrystyna, Sahu, Priyanka, Gao, Yijun, Li, Fei, Li, Fuming, Fang, Zhaoyuan, Jin, Yujuan, Gao, Juntao, Shi, Minglei, Sinha, Satrajit, Chen, Luonan, Chen, Yang, Kheoh, Thian, Yang, Wenjing, Yanai, Itai, Moreira, Andre L., Velcheti, Vamsidhar, Neel, Benjamin G., Hu, Liang, Christensen, James G., Olson, Peter, Gao, Dong, Zhang, Michael Q., Aguirre, Andrew J., Wong, Kwok-Kin, Ji, Hongbin
Publikováno v:
In Cancer Cell 11 March 2024 42(3):413-428