68 citations · 210 across the 41 of their papers we have counts for
9 papers · 1 filter
Functional Attentive Interpretable Regression
Haixu Wang, Tianyu Guan, Jiguo Cao
In function-on-function regression, the coefficient surface may exhibit complex support structure---from localized patches to global patterns such as disconnected regions,…
Probabilistic Functional Neural Networks
Haixu Wang, Jiguo Cao
High-dimensional functional time series (HDFTS) are often characterized by nonlinear trends and high spatial dimensions. Such data poses unique challenges for modeling and forecast…
Representation learning of dynamic networks
Haixu Wang, Jiguo Cao, Jian Pei
This study presents a novel representation learning model tailored for dynamic networks, which describes the continuously evolving relationships among individuals within a populati…
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…
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…
Neural Networks as Functional Classifiers
Barinder Thind, Kevin Multani, Jiguo Cao
In recent years, there has been considerable innovation in the world of predictive methodologies. This is evident by the relative domination of machine learning approaches in vario…
FuncNN: An R Package to Fit Deep Neural Networks Using Generalized Input Spaces
Barinder Thind, Sidi Wu, Richard Groenewald +1
Neural networks have excelled at regression and classification problems when the input space consists of scalar variables. As a result of this proficiency, several popular packages…
Deep Learning with Functional Inputs
Barinder Thind, Kevin Multani, Jiguo Cao
We present a methodology for integrating functional data into deep densely connected feed-forward neural networks. The model is defined for scalar responses with multiple functiona…
High-Dimensional Classification for Brain Decoding
Nicole Croteau, Farouk S. Nathoo, Jiguo Cao +1
Brain decoding involves the determination of a subject's cognitive state or an associated stimulus from functional neuroimaging data measuring brain activity. In this setting the c…