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autodp: A flexible and easy-to-use package for differential privacy
Differential privacy theory and code, differential private machine learning
Repository for collection of research papers on privacy.
Code for the paper "Bayesian Differential Privacy for Machine Learning"
Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more
Stock directionality using sentiment analysis and social media data. Created during Algothon 2019 at BlackRock.
Simple and practical private mean and covariance estimation. NeurIPS 2020.
Naive implementation of basic Differential-Privacy framework and algorithms
Everything you want about DP-Based Federated Learning, including Papers and Code. (Mechanism: Laplace or Gaussian, Dataset: femnist, shakespeare, mnist, cifar-10 and fashion-mnist. )
This repository contains all public data, python scripts, and documentation relating to NIST Public Safety Communications Research Division's Differential Privacy program including past prize challenges and bechmark problem sets.
This repo implements several algorithms for learning with differential privacy.
Code for Canonne-Kamath-Steinke paper https://arxiv.org/abs/2004.00010
code for 'Differential Location Privacy for Sparse Mobile Crowdsensing' at ICDM'16
Privacy-preserving data mining with decision tree
Differential priavcy based federated learning framework by various neural networks and svm using PyTorch.
Geopriv4j: An Open Source Repository for Practical Location Privacy
GFIM: An novel algorithm of frequent item mining with local differential privacy
Pytorch code for "Learning Implicit Generative Models by Matching Perceptual Features", ICCV 2019
Official implementation of "GS-WGAN: A Gradient-Sanitized Approach for Learning Differentially Private Generators" (NeurIPS 2020)
Experimental source code of HDPView
Applying Laplace and exponential mechanisms to add random noise to data for differential privacy. Plotting MSE vs. epsilon.
Code for visualizing the loss landscape of neural nets
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.