8 citations · 12 across the 4 of their papers we have counts for
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stat.ML2023
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…
stat.ML2022★ 8 cited
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…
stat.ML2021★ 4 cited
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…