awslabs / fast-differential-privacyView external linksLinks
Fast, memory-efficient, scalable optimization of deep learning with differential privacy
☆139Jan 22, 2026Updated 3 weeks ago
Alternatives and similar repositories for fast-differential-privacy
Users that are interested in fast-differential-privacy are comparing it to the libraries listed below
Sorting:
- A codebase that makes differentially private training of transformers easy.☆183Dec 9, 2022Updated 3 years ago
- ☆78May 28, 2022Updated 3 years ago
- Differentially-private transformers using HuggingFace and Opacus☆146Aug 28, 2024Updated last year
- Algorithms for Privacy-Preserving Machine Learning in JAX☆151Updated this week
- A fast algorithm to optimally compose privacy guarantees of differentially private (DP) mechanisms to arbitrary accuracy.☆76Feb 15, 2024Updated 2 years ago
- [ICML 2024] DPZero: Private Fine-Tuning of Language Models without Backpropagation☆16Sep 4, 2024Updated last year
- ☆15Jun 5, 2023Updated 2 years ago
- ☆25Apr 15, 2024Updated last year
- DP-Rewrite: Towards Reproducibility and Transparency in Differentially Private Text Rewriting☆15Apr 27, 2023Updated 2 years ago
- [ICML 2024 Spotlight] Differentially Private Synthetic Data via Foundation Model APIs 2: Text☆55Jan 11, 2025Updated last year
- Private Adaptive Optimization with Side Information (ICML '22)☆16Jun 23, 2022Updated 3 years ago
- Training PyTorch models with differential privacy☆1,903Nov 12, 2025Updated 3 months ago
- ☆28Nov 28, 2023Updated 2 years ago
- ☆10Jun 1, 2022Updated 3 years ago
- ☆15Apr 4, 2024Updated last year
- ☆12Jun 17, 2022Updated 3 years ago
- Computationally friendly hyper-parameter search with DP-SGD☆25Jan 7, 2025Updated last year
- ☆12Oct 2, 2023Updated 2 years ago
- Analytic calibration for differential privacy with Gaussian perturbations☆51Oct 7, 2018Updated 7 years ago
- ☆24Jan 10, 2024Updated 2 years ago
- This repo implements several algorithms for learning with differential privacy.☆110Dec 15, 2022Updated 3 years ago
- ☆21Sep 21, 2021Updated 4 years ago
- ☆12Jan 5, 2023Updated 3 years ago
- Code for computing tight guarantees for differential privacy☆23Mar 3, 2023Updated 2 years ago
- autodp: A flexible and easy-to-use package for differential privacy☆278Dec 5, 2023Updated 2 years ago
- [NeurIPS 2023] Differentially Private Image Classification by Learning Priors from Random Processes☆12Jun 12, 2023Updated 2 years ago
- A modern look at the relationship between sharpness and generalization [ICML 2023]☆43Sep 11, 2023Updated 2 years ago
- ☆13Oct 20, 2022Updated 3 years ago
- Privacy Meter: An open-source library to audit data privacy in statistical and machine learning algorithms.☆698Apr 26, 2025Updated 9 months ago
- Code for the paper "Evading Black-box Classifiers Without Breaking Eggs" [SaTML 2024]☆21Apr 15, 2024Updated last year
- A library providing general-purpose tools for estimating discrete distributions from noisy observations of their marginals.☆110Feb 9, 2026Updated last week
- PyTorch implementation of a number of mechanisms in local differential privacy☆17Feb 17, 2022Updated 3 years ago
- [ACL 2023] Knowledge Unlearning for Mitigating Privacy Risks in Language Models☆86Sep 12, 2024Updated last year
- Simulation framework for accelerating research in Private Federated Learning☆351Oct 24, 2025Updated 3 months ago
- ☆23Dec 15, 2022Updated 3 years ago
- Official repo for the paper: Recovering Private Text in Federated Learning of Language Models (in NeurIPS 2022)☆61Mar 13, 2023Updated 2 years ago
- TKDE'23: A Survey and Experimental Study on Privacy-Preserving Trajectory Data Publishing☆12May 5, 2023Updated 2 years ago
- Reference FOSS Policy for Financial Services Institutions☆13Mar 23, 2023Updated 2 years ago
- Code for Auditing DPSGD☆37Feb 15, 2022Updated 4 years ago