Authors: Sanguo Zhang, Xiaonan Hu, Ziye Luo, Yu Jiang, Yifan Sun, Shuangge Ma
arXiv
Heterogeneity is a hallmark of many complex diseases. There are multiple ways of defining heterogeneity, among which the heterogeneity in genetic regulations, for example GEs (gene expressions) by CNV...
Authors: Elnaz Yousefzadeh Barri, Steven Farber, Hadi Jahanshahi, Eda Beyazit
arXiv
Building an accurate model of travel behaviour based on individuals' characteristics and built environment attributes is of importance for policy-making and transportation planning. Recent experiments...
Authors: Arman Oganisian, Kelly D. Getz, Todd A. Alonzo, Richard Aplenc, Jason A. Roy
arXiv
We develop a Bayesian semi-parametric model for the estimating the impact of dynamic treatment rules on survival among patients diagnosed with pediatric acute myeloid leukemia (AML). The data consist...
Authors: Anamitra Saha, Sai Ravela
arXiv
Modeling the risk of extreme weather events in a changing climate is essential for developing effective adaptation and mitigation strategies. Although the available low-resolution climate models captu...
Authors: Zhong Wang, Yi Zhang, Yi Jiang
arXiv
Inspired by a sample lesson, this paper studies and discusses children's preferences in learning scientific concepts. In a "Dissolution" lesson, one of the students took the demonstration experiment o...
Authors: Yize Zhao, Changgee Chang, Jingwen Zhang, Zhengwu Zhang
arXiv
With distinct advantages in power over behavioral phenotypes, brain imaging traits have become emerging endophenotypes to dissect molecular contributions to behaviors and neuropsychiatric illnesses. A...
Authors: Zhong Wang, Zhen Cui, Yi Zhang
arXiv
The activation of scientific concepts (such as association) is not only an important way for children to organize scientific knowledges, but also an important way for them to learn complex concepts (s...
Authors: Saeed Maleki, Adhiti Raman, Yang Cheng, John Crassidis, Matthias Schmid
arXiv
This work provides a theoretical analysis for optimally solving the pose estimation problem using total least squares for vector observations from landmark features, which is central to applications i...
Authors: Rong Ma, Eric D. Sun, James Zou
arXiv
Dimension reduction and data visualization aim to project a high-dimensional dataset to a low-dimensional space while capturing the intrinsic structures in the data. It is an indispensable part of mod...
Authors: Ekaterina Morozova, Vladimir Panov
arXiv
In this paper, we present a new bivariate model for the joint description of the Bitcoin prices and the media attention to Bitcoin. Our model is based on the class of the LĂ©vy processes and is able to...
Authors: Yiming Hu, Yangchuan Huang, Shuying Liu, Yuanyang Qi, Danhui Bai
arXiv
Urban rail transit provides significant comprehensive benefits such as large traffic volume and high speed, serving as one of the most important components of urban traffic construction management and...
Authors: Sina Mews, Bastian Surmann, Lena Hasemann, Svenja Elkenkamp
arXiv
We explore Markov-modulated marked Poisson processes (MMMPPs) as a natural framework for modelling patients' disease dynamics over time based on medical claims data. In claims data, observations do no...
Authors: Ryan Joseph Worthen
arXiv
Major depressive disorder is a widespread mood disorder. One of the most debilitating symptoms patients often experience is cognitive impairment. Recent findings suggest that inflammation is associate...
Authors: Beat Neuenschwander, Simon Wandel, Satrajit Roychoudhury, Heinz Schmidli
arXiv
This paper focuses on the specification of the weights for the components of mixture priors.
Authors: Samy Mokhtari, Jean-Michel Badier, Christian G. Bénar, Bruno Torrésani
arXiv
This paper is concerned with variational and Bayesian approaches to neuro-electromagnetic inverse problems (EEG and MEG). The strong indeterminacy of these problems is tackled by introducing sparsity...