8 citations · 12 across the 4 of their papers we have counts for
4 papers
Semiparametric Regression for Spatial Data via Deep Learning
Kexuan Li, Jun Zhu, Anthony R. Ives +2
In this work, we propose a deep learning-based method to perform semiparametric regression analysis for spatially dependent data. To be specific, we use a sparsely connected deep n…
Deep Feature Screening: Feature Selection for Ultra High-Dimensional Data via Deep Neural Networks
Kexuan Li, Fangfang Wang, Lingli Yang +1
The applications of traditional statistical feature selection methods to high-dimension, low sample-size data often struggle and encounter challenging problems, such as overfitting…
Scalable Semiparametric Spatio-temporal Regression for Large Data Analysis
Ting Fung Ma, Fangfang Wang, Jun Zhu +2
With the rapid advances of data acquisition techniques, spatio-temporal data are becoming increasingly abundant in a diverse array of disciplines. Here we develop spatio-temporal r…
Calibrating multi-dimensional complex ODE from noisy data via deep neural networks
Kexuan Li, Fangfang Wang, Ruiqi Liu +2
Ordinary differential equations (ODEs) are widely used to model complex dynamics that arises in biology, chemistry, engineering, finance, physics, etc. Calibration of a complicated…