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pro vyhledávání: '"Wang, Linbo"'
Recent studies of two-view correspondence learning usually establish an end-to-end network to jointly predict correspondence reliability and relative pose. We improve such a framework from two aspects. First, we propose a Local Feature Consensus (LFC
Externí odkaz:
http://arxiv.org/abs/2308.03217
In many observational studies, researchers are often interested in studying the effects of multiple exposures on a single outcome. Standard approaches for high-dimensional data such as the lasso assume the associations between the exposures and the o
Externí odkaz:
http://arxiv.org/abs/2304.01098
Salient object detection segments attractive objects in scenes. RGB and thermal modalities provide complementary information and scribble annotations alleviate large amounts of human labor. Based on the above facts, we propose a scribble-supervised R
Externí odkaz:
http://arxiv.org/abs/2303.09733
We respond to comments on our paper, titled "Instrumental variable estimation of the causal hazard ratio."
Comment: To appear in Biometrics
Comment: To appear in Biometrics
Externí odkaz:
http://arxiv.org/abs/2210.13636
Autor:
Wang, Linbo
Applied researchers often claim that the risk difference is more heterogeneous than the relative risk and the odds ratio. Some also argue that there are theoretical grounds for why this claim is true. In this note, we point out that these arguments r
Externí odkaz:
http://arxiv.org/abs/2210.05179
Instrumental variable methods provide useful tools for inferring causal effects in the presence of unmeasured confounding. To apply these methods with large-scale data sets, a major challenge is to find valid instruments from a possibly large candida
Externí odkaz:
http://arxiv.org/abs/2203.09330
Publikováno v:
NeurIPS 2022
Multi-armed bandit problems provide a framework to identify the optimal intervention over a sequence of repeated experiments. Without additional assumptions, minimax optimal performance (measured by cumulative regret) is well-understood. With access
Externí odkaz:
http://arxiv.org/abs/2202.05100
Publikováno v:
In International Journal of Mechanical Sciences 15 June 2024 272
Autor:
Zhou, Cheng, You, Jia, Guan, Xiaojun, Guo, Tao, Wu, Jingjing, Wu, Haoting, Wu, Chenqing, Chen, Jingwen, Wen, Jiaqi, Tan, Sijia, Duanmu, Xiaojie, Qin, Jianmei, Huang, Peiyu, Zhang, Baorong, Cheng, Wei, Feng, Jianfeng, Xu, Xiaojun, Wang, Linbo, Zhang, Minming
Publikováno v:
In Neurobiology of Disease May 2024 194
Autor:
Zhang, Yuexia, Wang, Jian, Shen, Jiayi, Galloway-Pena, Jessica, Shelburne, Samuel, Wang, Linbo, Hu, Jianhua
Mediation analysis is an important tool to study causal associations in biomedical and other scientific areas and has recently gained attention in microbiome studies. Using a microbiome study of acute myeloid leukemia (AML) patients, we investigate w
Externí odkaz:
http://arxiv.org/abs/2110.02440