yanglabhkust Goto Github PK
Name: YangLab@HKUST
Type: Organization
Location: Hong Kong
Name: YangLab@HKUST
Type: Organization
Location: Hong Kong
hybrid representation learning approach for fully automatic and template-free vessel centerline extraction
A scalable Bayesian method for bi-level variable selection
BWMR (Bayesian Weighted Mendelian Randomization)
Collaborative Mixed Model
Deep Generative Learning via Schrödinger Bridge
Fast Integration of single-cell RNA-sequencing data across Multiple platforms
Flexible and Accurate Methods for Estimation and Inference of Gaussian Graphical Models with Applications
Quantifying the impact of genetically regulated expression on complex traits and diseases
Efficient statistical approach to characterize relationship among complex traits using summary statistics from multiple GWASs and functional annotations
Simulation codes to reproduce the results in the LPM paper
Efficient statistical approach to integrating functional annotations with genome-wide association studies
Simulation codes and example to reproduce the results in the LSMM paper
Tutorials for MATH 4432 Statistical Machine Learning, HKUST, Fall 2023
mfair: Matrix Factorization with Auxiliary Information in R
Mendelian Randomization accounting for Pleiotropy and Sample Structure using genome-wide summary statistics
R code for reproduce real data analysis in MRAPSS paper.
Adversarial domain translation networks for integrating large-scale atlas-level single-cell datasets
scPI: A scalable framework for probabilistic inference insingle-cell RNA-sequencing data analysis
Simulations in Bivas
Simulation codes in IGREX
A unified approach for integrating spatial and single-cell transcriptomics data by leveraging deep generative models
Measurement and comparison of several slices aligning methods and data integrating mathods for spatial transcriptomics data using several ST datasets.
Construction of a 3D whole organism spatial atlas by joint modeling of multiple slices
Code for "UCS: a unified approach to cell segmentation for subcellular spatial transcriptomics"
R package VCM contains three approaches for solving variance components model: PX-EM algorithm, MM algorithm and Method of Moments
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.