ObliviousAI / petlab_competition
🏁 The core repository to support participants through the UN PET Lab Hackathon 2022 👉 Registration at: https://petlab.officialstatistics.org/
☆19Updated 2 years ago
Related projects ⓘ
Alternatives and complementary repositories for petlab_competition
- ☆31Updated last year
- Tools and service for differentially private processing of tabular and relational data☆253Updated 3 months ago
- The core library of differential privacy algorithms powering the OpenDP Project.☆327Updated this week
- An implementation of the tools described in the paper entitled "Graphical-model based estimation and inference for differential privacy"☆92Updated this week
- ☆258Updated 7 months ago
- ☆39Updated last year
- The Python Differential Privacy Library. Built on top of: https://github.com/google/differential-privacy☆507Updated last month
- A software package for privacy-preserving generation of a synthetic twin to a given sensitive data set.☆47Updated 2 months ago
- SDNist: Benchmark data and evaluation tools for data synthesizers.☆31Updated 4 months ago
- A Unified Framework for Quantifying Privacy Risk in Synthetic Data according to the GDPR☆67Updated 4 months ago
- A toolbox for differentially private data generation☆129Updated last year
- Diffprivlib: The IBM Differential Privacy Library☆824Updated 3 weeks ago
- Code samples and documentation for SmartNoise differential privacy tools☆132Updated 2 years ago
- Comparing fairness-aware machine learning techniques.☆159Updated last year
- Python language bindings for smartnoise-core.☆75Updated last year
- Differentially Private (tabular) Generative Models Papers with Code☆43Updated 4 months ago
- PipelineDP is a Python framework for applying differentially private aggregations to large datasets using batch processing systems such a…☆275Updated 3 weeks ago
- ☆25Updated 10 months ago
- A hands-on tutorial showing how to use Python to do anonymisation with synthetic data☆78Updated 2 years ago
- pyCANON is a Python library and CLI to assess the values of the parameters associated with the most common privacy-preserving techniques.☆29Updated this week
- FairGrad, is an easy to use general purpose approach to enforce fairness for gradient descent based methods.☆14Updated last year
- FairPrep is a design and evaluation framework for fairness-enhancing interventions that treats data as a first-class citizen.☆11Updated last year
- A library that implements fairness-aware machine learning algorithms☆124Updated 4 years ago
- Evaluating variety of k-Anonymity techniques.☆53Updated last year
- Privacy Meter: An open-source library to audit data privacy in statistical and machine learning algorithms.☆603Updated this week
- Differential privacy validator and runtime☆290Updated 2 years ago
- A privacy preserving NLP framework☆198Updated last year
- Metrics to evaluate quality and efficacy of synthetic datasets.☆211Updated this week
- Editing machine learning models to reflect human knowledge and values☆123Updated last year
- Datasets derived from US census data☆240Updated 5 months ago