382 citations · 510 across the 17 of their papers we have counts for
9 papers · 1 filter
Distribution Preserving Graph Representation Learning
Chengsheng Mao, Yuan Luo
Graph neural network (GNN) is effective to model graphs for distributed representations of nodes and an entire graph. Recently, research on the expressive power of GNN attracted gr…
Constrained tensor factorization for computational phenotyping and mortality prediction in patients with cancer
Francisco Y Cai, Chengsheng Mao, Yuan Luo
Background: The increasing adoption of electronic health records (EHR) across the US has created troves of computable data, to which machine learning methods have been applied to e…
Non-Convex Optimization with Spectral Radius Regularization
Adam Sandler, Diego Klabjan, Yuan Luo
We develop regularization methods to find flat minima while training deep neural networks. These minima generalize better than sharp minima, yielding models outperforming baselines…
Towards Expressive Graph Representation
Chengsheng Mao, Liang Yao, Yuan Luo
Graph Neural Network (GNN) aggregates the neighborhood of each node into the node embedding and shows its powerful capability for graph representation learning. However, most exist…
Open-Set Recognition with Gaussian Mixture Variational Autoencoders
Alexander Cao, Yuan Luo, Diego Klabjan
In inference, open-set classification is to either classify a sample into a known class from training or reject it as an unknown class. Existing deep open-set classifiers train exp…
Conditional Hierarchical Bayesian Tucker Decomposition for Genetic Data Analysis
Adam Sandler, Diego Klabjan, Yuan Luo
We analyze large, multi-dimensional, sparse counting data sets, finding unsupervised groups to provide unique insights into genetic data. We create gene and biological pathway grou…
Mixture-based Multiple Imputation Model for Clinical Data with a Temporal Dimension
Ye Xue, Diego Klabjan, Yuan Luo
The problem of missing values in multivariable time series is a key challenge in many applications such as clinical data mining. Although many imputation methods show their effecti…
Identifying Sub-Phenotypes of Acute Kidney Injury using Structured and Unstructured Electronic Health Record Data with Memory Networks
Zhenxing Xu, Jingyuan Chou, Xi Sheryl Zhang +10
Acute Kidney Injury (AKI) is a common clinical syndrome characterized by the rapid loss of kidney excretory function, which aggravates the clinical severity of other diseases in a…
MedGCN: Medication recommendation and lab test imputation via graph convolutional networks
Chengsheng Mao, Liang Yao, Yuan Luo
Laboratory testing and medication prescription are two of the most important routines in daily clinical practice. Developing an artificial intelligence system that can automaticall…