68 citations · 210 across the 41 of their papers we have counts for
11 papers · 1 filter
A Joint Estimation Approach to Sparse Additive Ordinary Differential Equations
Nan Zhang, Muye Nanshan, Jiguo Cao
Ordinary differential equations (ODEs) are widely used to characterize the dynamics of complex systems in real applications. In this article, we propose a novel joint estimation ap…
Neural Networks for Scalar Input and Functional Output
Sidi Wu, Cédric Beaulac, Jiguo Cao
The regression of a functional response on a set of scalar predictors can be a challenging task, especially if there is a large number of predictors, or the relationship between th…
Random Competing Risks Forests for Large Data
Joel Therrien, Jiguo Cao
Random forests are a sensible non-parametric model to predict competing risk data according to some covariates. However, there are currently no packages that can adequately handle…
Neuroimaging Feature Extraction using a Neural Network Classifier for Imaging Genetics
Cédric Beaulac, Sidi Wu, Erin Gibson +5
A major issue in the association of genes to neuroimaging phenotypes is the high dimension of both genetic data and neuroimaging data. In this article, we tackle the latter problem…
Functional Nonlinear Learning
Haixu Wang, Jiguo Cao
Using representations of functional data can be more convenient and beneficial in subsequent statistical models than direct observations. These representations, in a lower-dimensio…
Dynamical Modeling for non-Gaussian Data with High-dimensional Sparse Ordinary Differential Equations
Muye Nanshan, Nan Zhang, Xiaolei Xun +1
Ordinary differential equations (ODE) have been widely used for modeling dynamical complex systems. For high-dimensional ODE models where the number of differential equations is la…
Predicting Time-to-conversion for Dementia of Alzheimer's Type using Multi-modal Deep Survival Analysis
Ghazal Mirabnahrazam, Da Ma, Cédric Beaulac +8
Dementia of Alzheimer's Type (DAT) is a complex disorder influenced by numerous factors, but it is unclear how each factor contributes to disease progression. An in-depth examinati…
Automatic Search Intervals for the Smoothing Parameter in Penalized Splines
Zheyuan Li, Jiguo Cao
The selection of smoothing parameter is central to the estimation of penalized splines. The best value of the smoothing parameter is often the one that optimizes a smoothness selec…
Stopping time detection of wood panel compression: A functional time series approach
H. L. Shang, J. Cao, P. Sang
We consider determining the optimal stopping time for the glue curing of wood panels in an automatic process environment. Using the near-infrared spectroscopy technology to monitor…
Machine Learning Based Multimodal Neuroimaging Genomics Dementia Score for Predicting Future Conversion to Alzheimer's Disease
Ghazal Mirabnahrazam, Da Ma, Sieun Lee +7
Background: The increasing availability of databases containing both magnetic resonance imaging (MRI) and genetic data allows researchers to utilize multimodal data to better under…
General P-Splines for Non-Uniform B-Splines
Zheyuan Li, Jiguo Cao
We proposed a new penalized B-splines estimator, the general P-spline, to accommodate non-uniform B-splines on unevenly spaced knots. It is a complement to Eilers and Marx's standa…