Alternatives and similar repositories for prv_accountant

Users that are interested in prv_accountant are comparing it to the libraries listed below

• jagielski / auditing-dpsgd
  Code for Auditing DPSGD
  ☆37Updated 3 years ago
• BorjaBalle / analytic-gaussian-mechanism
  Analytic calibration for differential privacy with Gaussian perturbations
  ☆48Updated 6 years ago
• ftramer / Handcrafted-DP
  ☆80Updated 3 years ago
• google-deepmind / jax_privacy
  Algorithms for Privacy-Preserving Machine Learning in JAX
  ☆96Updated last month
• facebookresearch / label_dp_antipodes
  Code to reproduce experiments in "Antipodes of Label Differential Privacy PATE and ALIBI"
  ☆32Updated 3 years ago
• lxuechen / private-transformers
  A codebase that makes differentially private training of transformers easy.
  ☆175Updated 2 years ago
• awslabs / fast-differential-privacy
  Fast, memory-efficient, scalable optimization of deep learning with differential privacy
  ☆127Updated last week
• yuxiangw / autodp
  autodp: A flexible and easy-to-use package for differential privacy
  ☆274Updated last year
• bargavj / EvaluatingDPML
  This project's goal is to evaluate the privacy leakage of differentially private machine learning models.
  ☆135Updated 2 years ago
• spring-epfl / mia
  A library for running membership inference attacks against ML models
  ☆149Updated 2 years ago
• huseyinatahaninan / Differentially-Private-Fine-tuning-of-Language-Models
  ☆75Updated 3 years ago
• microsoft / dp-transformers
  Differentially-private transformers using HuggingFace and Opacus
  ☆140Updated 11 months ago
• dayu11 / Differentially-Private-Deep-Learning
  This repo implements several algorithms for learning with differential privacy.
  ☆109Updated 2 years ago
• google-research / DP-FTRL
  DP-FTRL from "Practical and Private (Deep) Learning without Sampling or Shuffling" for centralized training.
  ☆30Updated 2 months ago
• IBM / discrete-gaussian-differential-privacy
  Code for Canonne-Kamath-Steinke paper https://arxiv.org/abs/2004.00010
  ☆59Updated 5 years ago
• inspire-group / membership-inference-evaluation
  Systematic Evaluation of Membership Inference Privacy Risks of Machine Learning Models
  ☆127Updated last year
• woodyx218 / opacus_global_clipping
  ☆15Updated 2 years ago
• csong27 / property-inference-collaborative-ml
  Code for Exploiting Unintended Feature Leakage in Collaborative Learning (in Oakland 2019)
  ☆54Updated 6 years ago
• AI-secure / G-PATE
  [NeurIPS 2021] "G-PATE: Scalable Differentially Private Data Generator via Private Aggregation of Teacher Discriminators" by Yunhui Long*…
  ☆30Updated 3 years ago
• facebookresearch / Opacus-lab
  Research and experimental code related to Opacus, an open-source library for training PyTorch models with Differential Privacy
  ☆18Updated 10 months ago
• dayu11 / Gradient-Embedding-Perturbation
  ☆27Updated 2 years ago
• JialinMao / private_CNN
  ☆10Updated 3 years ago
• ebagdasa / pytorch-privacy
  simple Differential Privacy in PyTorch
  ☆48Updated 5 years ago
• ryan112358 / mbi
  A library providing general-purpose tools for estimating discrete distributions from noisy observations of their marginals.
  ☆105Updated 2 weeks ago
• sunblaze-ucb / dpml-benchmark
  This repository contains the codes for first large-scale investigation of Differentially Private Convex Optimization algorithms.
  ☆63Updated 6 years ago
• jinyuan-jia / MemGuard
  ☆45Updated 5 years ago
• BorjaBalle / amplification-by-shuffling
  Implementation of calibration bounds for differential privacy in the shuffle model
  ☆22Updated 4 years ago
• ebagdasa / differential-privacy-vs-fairness
  Code for "Differential Privacy Has Disparate Impact on Model Accuracy" NeurIPS'19
  ☆33Updated 4 years ago
• csong27 / membership-inference
  Code for Membership Inference Attack against Machine Learning Models (in Oakland 2017)
  ☆193Updated 7 years ago
• sam-yeom / ml-privacy-csf18
  Code for the CSF 2018 paper "Privacy Risk in Machine Learning: Analyzing the Connection to Overfitting"
  ☆37Updated 6 years ago