9 citations · 21 across the 8 of their papers we have counts for
11 papers
Calibrated Transfer Learning for Survival Prediction and Treatment Inference
Shuoyang Wang, Wanyu Zhang, Lingli Yang +1
Historical survival data can improve prediction in a cohort with few events, but prognostic differences can make borrowing harmful. To borrow while adapting, we propose calibrated…
Adaptive Sampling of Costly Outcomes in Randomized Clinical Trials
Shuoyang Wang, Wanyu Zhang, Lingli Yang +1
In some randomized trials the primary outcome is costly or slow to measure, while auxiliary variables that predict it are available for everyone. The outcome can then be measured i…
Empowering Multi-class Classification for Multivariate Functional Data with Simultaneous Feature Selection
Shuoyang Wang, Guanqun Cao, Yuan Huang
The opportunity to utilize complex functional data types for conducting classification tasks is emerging with the growing availability of imaging data. However, the tools capable o…
Multiclass classification for multidimensional functional data through deep neural networks
Shuoyang Wang, Guanqun Cao
The intrinsically infinite-dimensional features of the functional observations over multidimensional domains render the standard classification methods effectively inapplicable. To…
Minimax optimal high-dimensional classification using deep neural networks
Shuoyang Wang, Zuofeng Shang
High-dimensional classification is a fundamentally important research problem in high-dimensional data analysis. In this paper, we derive a nonasymptotic rate for the minimax exces…
Robust Deep Neural Network Estimation for Multi-dimensional Functional Data
Shuoyang Wang, Guanqun Cao
In this paper, we propose a robust estimator for the location function from multi-dimensional functional data. The proposed estimators are based on the deep neural networks with Re…
Deep Neural Network Classifier for Multi-dimensional Functional Data
Shuoyang Wang, Guanqun Cao, Zuofeng Shang
We propose a new approach, called as functional deep neural network (FDNN), for classifying multi-dimensional functional data. Specifically, a deep neural network is trained based…
Optimal Classification for Functional Data
Shuoyang Wang, Zuofeng Shang, Guanqun Cao +1
A central topic in functional data analysis is how to design an optimaldecision rule, based on training samples, to classify a data function. We exploit the optimal classification…
Estimation of the Mean Function of Functional Data via Deep Neural Networks
Shuoyang Wang, Guanqun Cao, Zuofeng Shang
In this work, we propose a deep neural network method to perform nonparametric regression for functional data. The proposed estimators are based on sparsely connected deep neural n…
Diffusion regions and 3D energy mode development in spontaneous reconnection
Shuoyang Wang, Takaaki Yokoyama
The understanding of magnetic reconnection in three-dimension (3D) is far shallower than its counterpart in two-dimension (2D) due to its potential complication, not to mention the…
Three-Dimensional MHD Magnetic Reconnection Simulations with Finite Guide Field: Proposal of the Shock-Evoking Positive-Feedback Model
Shuoyang Wang, Takaaki Yokoyama, Hiroaki Isobe
Using a three-dimensional magnetohydrodynamic model, we simulate the magnetic reconnection in a single current sheet. We assume a finite guide field, a random perturbation on the v…