zhenkewu
Associate Prof of Biostat UMichigan; AI for Individualized health. The future is already here — it’s just not very evenly distributed. -William Gibson
University of MichiganAnn Arbor, Michigan, USA
Pinned Repositories
synthEHRella
SynthEHRella is a benchmarking package used for evaluating synthetic Electronic Health Records (EHR) data generation methods.
baker
👩🍳 🥧 Bayesian Analysis Kit for Etiology Research via Nested Partially Latent Class Models
baker_example
Example Code for 'baker' Package
bugs.models
.bug files for use in WinBUGS or OpenBUGS model fitting
ddtlcm
Tree-regularized latent class models to improve estimation under weak separation and small sample sizes
demo_code
Demonstration code for small problems
doubletree
🎄🎄 Nested Latent Class Models for Domain-Adaptive and Semi-supervised Learning of Cause-of-Deaths using Verbal Autopsy
lotR
🌲 Integrating Sample Similarity Information into Latent Class Models: A Tree-Structured Shrinkage Approach
nplcm
R package for fitting nested partially latent class models (nplcm)
zhenkewu.github.io
Zhenke Wu, PhD Research Website
zhenkewu's Repositories
zhenkewu/baker
👩🍳 🥧 Bayesian Analysis Kit for Etiology Research via Nested Partially Latent Class Models
zhenkewu/zhenkewu.github.io
Zhenke Wu, PhD Research Website
zhenkewu/bugs.models
.bug files for use in WinBUGS or OpenBUGS model fitting
zhenkewu/nplcm
R package for fitting nested partially latent class models (nplcm)
zhenkewu/baker_example
Example Code for 'baker' Package
zhenkewu/demo_code
Demonstration code for small problems
zhenkewu/doubletree
🎄🎄 Nested Latent Class Models for Domain-Adaptive and Semi-supervised Learning of Cause-of-Deaths using Verbal Autopsy
zhenkewu/spotgear
🔭 Subset Profiling and Organizing Tools for Gel Electrophoresis Autoradiography in R
zhenkewu/ddtlcm
Tree-regularized latent class models to improve estimation under weak separation and small sample sizes
zhenkewu/lotR
🌲 Integrating Sample Similarity Information into Latent Class Models: A Tree-Structured Shrinkage Approach
zhenkewu/rewind
⏪ R package for: Reconstructing Etiology with Binary Decomposition
zhenkewu/adv-r
Advanced R programming: a book
zhenkewu/CUSUM-RL
Implementation of "Reinforcement Learning in Possibly Nonstationary Environments"
zhenkewu/ddtlcm_shiny
zhenkewu/genAI
learning and implementing generative AI tools
zhenkewu/LCVA
Nested latent class model for Verbal Autopsy
zhenkewu/MediationRL
Implementation of "A Reinforcement Learning Framework for Dynamic Mediation Analysis" (ICML 2023) in Python.
zhenkewu/mpcr
R package for estimating treatment effects in matched-pair cluster randomized trials (MPCR) using covariate calibration
zhenkewu/MRT
Micro randomized trial with peer effects
zhenkewu/ormachine
zhenkewu/r-pkgs
Building R packages
zhenkewu/RxTree
zhenkewu/scalable-bayesian-inference-papers
zhenkewu/slamR
Fast Algorithms for Fitting Structured Latent Attribute Models (SLAM) in R
zhenkewu/slvm_va
build and test structured latent variable models for verbal autopsy data that do regression, scale to large data sizes and work in the absence of gold-standard data
zhenkewu/synthEHRella
SynthEHRella is a benchmarking package used for evaluating synthetic Electronic Health Records (EHR) data generation methods.
zhenkewu/ultrametricMat
The ultrametricMat is a package designed to conduct the Bayesian inference on the ultrametric matrices by the leveraging the bijection map between the ultrametric matrices and the tree space. We refer to more details to Yao et al. (2023+) Geometry-driven Bayesian Inference for Ultrametric Covariance Matrices.