Zobrazeno 1 - 10
of 668
pro vyhledávání: '"Xu Ronghui"'
In observational studies with delayed entry, causal inference for time-to-event outcomes can be challenging. The challenges arise because, in addition to the potential confounding bias from observational data, the collected data often also suffers fr
Externí odkaz:
http://arxiv.org/abs/2411.18879
Autor:
Xu, Ronghui, Cheng, Hanyin, Guo, Chenjuan, Gao, Hongfan, Hu, Jilin, Yang, Sean Bin, Yang, Bin
Developing effective path representations has become increasingly essential across various fields within intelligent transportation. Although pre-trained path representation learning models have shown improved performance, they predominantly focus on
Externí odkaz:
http://arxiv.org/abs/2411.18428
Autor:
Tian, Jindong, Liang, Yuxuan, Xu, Ronghui, Chen, Peng, Guo, Chenjuan, Zhou, Aoying, Pan, Lujia, Rao, Zhongwen, Yang, Bin
Air pollution significantly threatens human health and ecosystems, necessitating effective air quality prediction to inform public policy. Traditional approaches are generally categorized into physics-based and data-driven models. Physics-based model
Externí odkaz:
http://arxiv.org/abs/2410.19892
Probabilistic time series imputation has been widely applied in real-world scenarios due to its ability to estimate uncertainty of imputation results. Meanwhile, denoising diffusion probabilistic models (DDPMs) have achieved great success in probabil
Externí odkaz:
http://arxiv.org/abs/2410.13338
We consider time to treatment initialization. This can commonly occur in preventive medicine, such as disease screening and vaccination; it can also occur with non-fatal health conditions such as HIV infection without the onset of AIDS; or in tech in
Externí odkaz:
http://arxiv.org/abs/2409.13097
Significant wave height (SWH) is a vital metric in marine science, and accurate SWH estimation is crucial for various applications, e.g., marine energy development, fishery, early warning systems for potential risks, etc. Traditional SWH estimation m
Externí odkaz:
http://arxiv.org/abs/2407.20053
The availability of massive vehicle trajectory data enables the modeling of road-network constrained movement as travel-cost distributions rather than just single-valued costs, thereby capturing the inherent uncertainty of movement and enabling impro
Externí odkaz:
http://arxiv.org/abs/2407.06881
With the proliferation of mobile sensing techniques, huge amounts of time series data are generated and accumulated in various domains, fueling plenty of real-world applications. In this setting, time series anomaly detection is practically important
Externí odkaz:
http://arxiv.org/abs/2406.02318
In this paper we address the challenges posed by non-proportional hazards and informative censoring, offering a path toward more meaningful causal inference conclusions. We start from the marginal structural Cox model, which has been widely used for
Externí odkaz:
http://arxiv.org/abs/2311.07752
We consider a general proportional odds model for survival data under binary treatment, where the functional form of the covariates is left unspecified. We derive the efficient score for the conditional survival odds ratio given the covariates using
Externí odkaz:
http://arxiv.org/abs/2310.14448