shu-hai Goto Github PK
Name: Hai Shu
Type: User
Name: Hai Shu
Type: User
The implementation of 3D_DenseSeg for infant brain MRI segmentation
Framework for the reproducible classification of Alzheimer's disease using machine learning
This repository provides the AJIVE software in Matlab and all related Matlab scripts to reproduce the results in the paper Angle-basied Joint And Individual Variation Explained (Feng et.al., 2018). Please refer to README.md for instruction.
Bug-tracking for Jeff's algorithms book, notes, etc.
List of software packages for multi-omics analysis
PyTorch implementation of "Weight Uncertainty in Neural Networks"
Notebooks related to Bayesian methods for machine learning
Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace and more
Bayesian Weight Uncertainty Dense Layer for Keras
Bayesian Data Analysis course at Aalto
Bayesian Data Analysis demos for R
🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.
This repo is the source code for [BiTr-Unet: a CNN-Transformer Combined Network for MRI Brain Tumor Segmentation].
Breast density classification with deep convolutional neural networks
Fully automated breast segmentation on Mammographies.
CDPA: Common and Distinctive Pattern Analysis between High-dimensional Datasets (EJS-22 paper)
Software platform for clinical neuroimaging studies
CRF-RNN Keras/Tensorflow version
:books: Computer Science Learning Notes
A Decomposition-based Canonical Correlation Analysis for High-dimensional Datasets (JASA-20 paper)
Decomposition-based Generalized Canonical Correlation Analysis for Multi-view High-dimensional Data (JMLR-22 paper)
Deep Learning Papers on Medical Image Analysis
List of papers, code and experiments using deep learning for time series forecasting
Zhu, Wentao, Qi Lou, Yeeleng Scott Vang, and Xiaohui Xie. "Deep Multi-instance Networks with Sparse Label Assignment for Whole Mammogram Classification." MICCAI 2017.
The Deep Weight Prior, ICLR 2019
深度学习500问,以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述,以帮助自己及有需要的读者。 全书分为15个章节,近20万字。由于水平有限,书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作,联系[email protected] 版权所有,违权必究 Tan 2018.06
A demonstration of reproducing the analysis from a genome wide association study (GWAS)
Fully-connected (dense) 3D CRF for processing biomedical scans
The Digital Mammography DREAM Challenge
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.