hengshiyu
Graduate Student in Machine Learning, Computational Biology
University of Michigan, Ann ArborAnn Arbor, Michigan, USA
Pinned Repositories
chemical_vae
Code for 10.1021/acscentsci.7b00572, now running on Keras 2.0 and Tensorflow
cvcrand
An R package for covariate-constrained randomization and clustered permutation test for cluster randomized trials
deepchem
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
geeCpp
A C++ package for generalized estimating equations (GEE)
geeCRT
An R package for implementing the bias-corrected generalized estimating equations in analyzing cluster randomized trials
hengshiyu
hengshiyu.github.io
Build a Jekyll blog in minutes, without touching the command line.
stochastic-Q-learning
Stochastic Q Learning for Estimation on Dynamic Treatment Regimes for Reinforcement Learning
MichiGAN
Learning disentangled representations of single-cell data for high-quality generation
PerturbNet
PerturbNet is a deep generative model that can predict the distribution of cell states induced by chemical or genetic perturbation
hengshiyu's Repositories
hengshiyu/geeCRT
An R package for implementing the bias-corrected generalized estimating equations in analyzing cluster randomized trials
hengshiyu/chemical_vae
Code for 10.1021/acscentsci.7b00572, now running on Keras 2.0 and Tensorflow
hengshiyu/cvcrand
An R package for covariate-constrained randomization and clustered permutation test for cluster randomized trials
hengshiyu/deepchem
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
hengshiyu/geeCpp
A C++ package for generalized estimating equations (GEE)
hengshiyu/hengshiyu
hengshiyu/hengshiyu.github.io
Build a Jekyll blog in minutes, without touching the command line.
hengshiyu/stochastic-Q-learning
Stochastic Q Learning for Estimation on Dynamic Treatment Regimes for Reinforcement Learning
hengshiyu/pytorch_geometric
Geometric Deep Learning Extension Library for PyTorch
hengshiyu/Random-Forest-Kernel
Random forest kernel: nonparametric learning of kernel causal effects
hengshiyu/scgen
Single cell perturbation prediction
hengshiyu/scvi-tools
Deep probabilistic analysis of single-cell omics data
hengshiyu/umich-eecs545-lectures
This repository contains the lecture materials for EECS 545, a graduate course in Machine Learning, at the University of Michigan, Ann Arbor.