Pytorch implementation of paper Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data (https://arxiv.org/abs/1610.05755)
☆46Nov 29, 2021Updated 4 years ago
Alternatives and similar repositories for PATE
Users that are interested in PATE are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- [NeurIPS 2021] "G-PATE: Scalable Differentially Private Data Generator via Private Aggregation of Teacher Discriminators" by Yunhui Long*…☆30Oct 26, 2021Updated 4 years ago
- Local Differential Privacy for Federated Learning☆19Oct 24, 2022Updated 3 years ago
- Naive implementation of basic Differential-Privacy framework and algorithms☆49Aug 30, 2022Updated 3 years ago
- ☆10Jun 1, 2022Updated 4 years ago
- [CCS 2021] "DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation" by Boxin Wang*, Fan Wu*, Yunhui Long…☆36Dec 28, 2021Updated 4 years ago
- Managed Database hosting by DigitalOcean • AdPostgreSQL, MySQL, MongoDB, Kafka, Valkey, and OpenSearch available. Automatically scale up storage and focus on building your apps.
- Code to accompany the paper "Deep Learning with Gaussian Differential Privacy"☆49Apr 29, 2021Updated 5 years ago
- ☆24Apr 29, 2022Updated 4 years ago
- Code for Exploiting Unintended Feature Leakage in Collaborative Learning (in Oakland 2019)☆56May 28, 2019Updated 7 years ago
- ☆10Oct 18, 2021Updated 4 years ago
- autodp: A flexible and easy-to-use package for differential privacy☆279Dec 5, 2023Updated 2 years ago
- Locally Private Graph Neural Networks (ACM CCS 2021)☆50Jun 10, 2026Updated 3 weeks ago
- (IJCAI 2019) Knowledge Amalgamation from Heterogeneous Networks by Common Feature Learning☆10Nov 25, 2022Updated 3 years ago
- Code for the paper: Label-Only Membership Inference Attacks☆68Sep 11, 2021Updated 4 years ago
- Training PyTorch models with differential privacy☆1,939Updated this week
- Simple, predictable pricing with DigitalOcean hosting • AdAlways know what you'll pay with monthly caps and flat pricing. Enterprise-grade infrastructure trusted by 600k+ customers.
- privacy preserving deep learning☆15Sep 11, 2017Updated 8 years ago
- Library for training machine learning models with privacy for training data☆2,015Updated this week
- Differential Privacy Preservation in Deep Learning under Model Attacks☆135Apr 16, 2021Updated 5 years ago
- Differential privacy implementation in the Java family of languages (Java, Kotlin, Scala etc...)☆11Aug 31, 2020Updated 5 years ago
- Differentially Private Clustering in High-Dimensional Euclidean Spaces☆12Dec 30, 2017Updated 8 years ago
- Template for building 2D grid worlds with OpenAI Gym and Pycolab☆14Jun 12, 2019Updated 7 years ago
- 建立基于差分隐私的贝叶斯网络,使得结构化数据同时兼备隐私性与效用性☆30Jan 31, 2021Updated 5 years ago
- A codebase that makes differentially private training of transformers easy.☆190Dec 9, 2022Updated 3 years ago
- Code for paper "Byzantine-Resilient Distributed Finite-Sum Optimization over Networks"☆18Nov 5, 2020Updated 5 years ago
- Managed Database hosting by DigitalOcean • AdPostgreSQL, MySQL, MongoDB, Kafka, Valkey, and OpenSearch available. Automatically scale up storage and focus on building your apps.
- Code for Active Mixup in 2020 CVPR☆23Jan 11, 2022Updated 4 years ago
- ☆36Jan 5, 2022Updated 4 years ago
- simple Differential Privacy in PyTorch☆49May 29, 2020Updated 6 years ago
- Code for the CSF 2018 paper "Privacy Risk in Machine Learning: Analyzing the Connection to Overfitting"☆38Jan 28, 2019Updated 7 years ago
- DP-HyperparamTuning offers an array of tools for fast and easy hypertuning of various hyperparameters for the DP-SGD algorithm.☆23Sep 27, 2021Updated 4 years ago
- Differentially Private Deep Learning in PyTorch☆30Sep 27, 2021Updated 4 years ago
- ☆19Mar 6, 2023Updated 3 years ago
- Simplified implementation of federated learning in PyTorch☆32Jan 7, 2021Updated 5 years ago
- Differentially Private Federated Learning on Heterogeneous Data☆77Feb 22, 2022Updated 4 years ago
- Deploy to Railway using AI coding agents - Free Credits Offer • AdUse Claude Code, Codex, OpenCode, and more. Autonomous software development now has the infrastructure to match with Railway.
- A library for running membership inference attacks against ML models☆151Dec 8, 2022Updated 3 years ago
- Repository for Federated Learning with Differential Privacy☆11May 28, 2022Updated 4 years ago
- Official Code for CVPR 2024 paper: Permutation Equivariance of Transformers and Its Applications.☆17Nov 12, 2024Updated last year
- Privacy Risks of Securing Machine Learning Models against Adversarial Examples☆47Nov 25, 2019Updated 6 years ago
- Code for the paper "ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models"☆86Nov 22, 2021Updated 4 years ago
- Implementation of membership inference and model inversion attacks, extracting training data information from an ML model. Benchmarking …☆103Nov 2, 2019Updated 6 years ago
- AutoML, Privacy Preserving, Federated Learning☆27Jun 8, 2023Updated 3 years ago