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A collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explanation/interpretability. Analysis of incorporating label feedback with ensemble and tree-based detectors. Includes adversarial attacks with Graph Convolutional Network.
A recommender system for GNU/Linux applications
A curated list of awesome adversarial machine learning resources
A collection of AWESOME things about domian adaptation
A curated list of awesome imbalanced learning papers, codes, frameworks, and libraries. | 类别不平衡学习:论文、代码、框架与库
This is a list of awesome demos, tutorials, utilities and overall resources for the robotics community that use MATLAB and Simulink.
A curated list of time series augmentation resources.
A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.
A curated list of awesome self-supervised methods
Best transfer learning and domain adaptation resources (papers, tutorials, datasets, etc.)
Bayesian Neural Networks, Deep generative networks, Artificial general intelligence
MCMC routines
北航毕设论文LaTeX模板
Causal Effect Inference with Deep Latent-Variable Models
List of useful data augmentation resources. You will find here some not common techniques, libraries, links to github repos, papers and others.
Deep Active Learning
Notes and experiments to understand deep learning concepts
List of papers, code and experiments using deep learning for time series forecasting
The basic distribution probability Tutorial for Deep Learning Researchers
Source codes for the paper "Deep Learning Algorithms for Rotating Machinery Intelligent Diagnosis: An Open Source Benchmark Study"
Personalized Fashion Recommendation and Generation
Cloned from http://triton.inf-cv.uni-jena.de/LifelongLearning/gpEMOC
Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.
An MCMC algorithm for sampling continuous probability distributions in parallel
Must-read papers on graph neural networks (GNN)
A framework for large-scale machine learning and graph computation.
Image augmentation for machine learning experiments.
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.