papers
Publications (13)
math.NA2026
A Penalty-Free Asymmetric Nitsche's Method for Edge Elements
Tianwei Yu
stat.ML2018
A graph-embedded deep feedforward network for disease outcome classification and feature selection using gene expression data
Yunchuan Kong, Tianwei Yu
stat.AP2021
Autoencoder-based integrative multi-omics data embedding that allows for confounder adjustments
Tianwei Yu
stat.ME2018
Bayesian network marker selection via the thresholded graph Laplacian Gaussian prior
Qingpo Cai, Jian Kang, Tianwei Yu
cs.LG2026
Learning, Solving and Optimizing PDEs with TensorGalerkin: an efficient high-performance Galerkin assembly algorithm
Shizheng Wen, Mingyuan Chi, Tianwei Yu +5
stat.ME2024
Bayesian Functional Analysis for Untargeted Metabolomics Data with Matching Uncertainty and Small Sample Sizes
Guoxuan Ma, Jian Kang, Tianwei Yu
stat.ML2018
Nonlinear variable selection with continuous outcome: a nonparametric incremental forward stagewise approach
Tianwei Yu
stat.ML2026
Fast Gibbs Sampling on Bayesian Hidden Markov Model with Missing Observations
Dongrong Li, Tianwei Yu, Xiaodan Fan
math.NA2026
A Mixed Finite Element Method for the Dirichlet Vector Laplacian in Three Dimensions
Ralf Hiptmair, Peiyang Yu, Tianwei Yu
stat.ML2019
forgeNet: A graph deep neural network model using tree-based ensemble classifiers for feature extraction
Yunchuan Kong, Tianwei Yu
cs.LG2026
CC-AOS: Cost- and Horizon-Conditioned Amortized Backward Induction for Finite-Horizon Optimal Stopping
Tianwei Yu
stat.AP2017
DCA: Dynamic Correlation Analysis
Tianwei Yu
stat.AP2014
A Bayesian nonparametric mixture model for selecting genes and gene subnetworks
Yize Zhao, Jian Kang, Tianwei Yu