6 papers
AI-Augmented Statistical Network Estimation with Proxy Gene Embeddings
Yan Chen, Weijing Tang, Jin-Hong Du
Gene--gene networks are often observed only on a restricted target set, while modern biomedical foundation models provide proxy gene embeddings over substantially larger gene unive…
Nonparametric Inference for Balance in Signed Networks
Xuyang Chen, Yinjie Wang, Weijing Tang
In many real-world networks, relationships often go beyond simple dyadic presence or absence; they can be positive, like friendship, alliance, and mutualism, or negative, character…
Mini-batch Estimation for Deep Cox Models: Statistical Foundations and Practical Guidance
Lang Zeng, Weijing Tang, Zhao Ren +1
The stochastic gradient descent (SGD) algorithm has been widely used to optimize deep Cox neural network (Cox-NN) by updating model parameters using mini-batches of data. We show t…
Knowledge-Embedded Latent Projection for Robust Representation Learning
Weijing Tang, Ming Yuan, Zongqi Xia +1
Latent space models are widely used for analyzing high-dimensional discrete data matrices, such as patient-feature matrices in electronic health records (EHRs), by capturing comple…
Balanced Stochastic Block Model for Community Detection in Signed Networks
Yichao Chen, Weijing Tang, Ji Zhu
Community detection, discovering the underlying communities within a network from observed connections, is a fundamental problem in network analysis, yet it remains underexplored f…
DANIEL: A Distributed and Scalable Approach for Global Representation Learning with EHR Applications
Zebin Wang, Ziming Gan, Weijing Tang +4
Classical probabilistic graphical models face fundamental challenges in modern data environments, which are characterized by high dimensionality, source heterogeneity, and stringen…