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Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
https://baobablab.github.io/baobab/
A deep learning model to predict individual brain ages from MRI datasets
Predict age from brain anatomy measures of Grey Matter (GM) volumes using Deep Learning.
Age prediction with site-effect removal: A challenge on the openBHB dataset that aims to i) predict age from derived 3D T1w anatomical MRI data while ii) removing site/scanner information from the learned representation.
Logic CubicWeb cube
Easy to use pure-python caller signature and profiler.
Collaborative Analysis Platform : Simple, Unifying, Lean
Deep Clustering for Unsupervised Learning of Visual Features
A Variational Information Bottleneck Approach to Multi-Omics Data Integration
A list of deep learning implementations in biology
Main model and preprocessing code
Code for the CIKM 2019 paper "DSANet: Dual Self-Attention Network for Multivariate Time Series Forecasting".
job CATI
Towards Gene Expression Convolutions using Gene Interaction Graphs
heritability analysis with multidimensional matrices
A Generative Discriminative Framework that Integrates Imaging, Genetic, andDiagnosis Data into Coupled Low Dimensional Space
Reference deployment of JupyterHub with docker
A configuration for a JupyterHub+DockerSpawner+OAuth2 server with Traefik proxy, based on docker-compose
Multivariate Functional Shape Data Analysis in Python (MFSDA_Python) is a Python based package for statistical shape analysis. A multivariate varying coefficient model is introduced to build the association between the multivariate shape measurements and demographic information and other clinical, biological variables. Statistical inference, i.e., hypothesis testing, is also included in this package, which can be used in investigating whether some covariates of interest are significantly associated with the shape information. The hypothesis testing results are further used in clustering based analysis, i.e., significant suregion detection. This MFSDA package is developed by Chao Huang and Hongtu Zhu from the BIG-S2 lab.
MGN-Net: A novel Graph Neural Network for integrating heterogenous graph population derived from multiple sources.
Machine learning for NeuroImaging in Python
Workflows and interfaces for neuroimaging packages
Curated list of open-access databases with human structural MRI data
Summaries of machine learning papers
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.