Alternatives and similar repositories for DP-MERF

Users that are interested in DP-MERF are comparing it to the libraries listed below

• 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
• DingfanChen / GS-WGAN
  Official implementation of "GS-WGAN: A Gradient-Sanitized Approach for Learning Differentially Private Generators" (NeurIPS 2020)
  ☆69Updated 2 years ago
• jeremy43 / Private_kNN
  ☆24Updated 3 years ago
• AI-secure / DataLens
  [CCS 2021] "DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation" by Boxin Wang*, Fan Wu*, Yunhui Long…
  ☆37Updated 3 years ago
• facebookresearch / whitebox_blackbox
  Public implementation of ICML'19 paper "White-box vs Black-box: Bayes Optimal Strategies for Membership Inference"
  ☆16Updated 4 years ago
• woodyx218 / opacus_global_clipping
  ☆15Updated last year
• JialinMao / private_CNN
  ☆10Updated 2 years ago
• ftramer / Handcrafted-DP
  ☆80Updated 2 years ago
• facebookresearch / label_dp_antipodes
  Code to reproduce experiments in "Antipodes of Label Differential Privacy PATE and ALIBI"
  ☆31Updated 3 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
• jagielski / auditing-dpsgd
  Code for Auditing DPSGD
  ☆37Updated 3 years ago
• ebagdasa / pytorch-privacy
  simple Differential Privacy in PyTorch
  ☆48Updated 4 years ago
• JunyiZhu-AI / R-GAP
  R-GAP: Recursive Gradient Attack on Privacy [Accepted at ICLR 2021]
  ☆36Updated 2 years ago
• microsoft / prv_accountant
  A fast algorithm to optimally compose privacy guarantees of differentially private (DP) mechanisms to arbitrary accuracy.
  ☆73Updated last year
• ganevgv / dp-generative-models
  Differentially Private (tabular) Generative Models Papers with Code
  ☆48Updated 10 months ago
• illidanlab / dpgan
  Source code of paper "Differentially Private Generative Adversarial Network"
  ☆69Updated 6 years ago
• google-deepmind / jax_privacy
  Algorithms for Privacy-Preserving Machine Learning in JAX
  ☆94Updated 3 weeks ago
• mkhodak / FedEx
  ☆12Updated 3 years ago
• Machine-Learning-Security-Lab / mia_prune
  Membership Inference Attacks and Defenses in Neural Network Pruning
  ☆28Updated 2 years ago
• frhrdr / patepy
  A simple wrapper for the PATE analysis for Differential Privacy by Papernot, Song et al.
  ☆9Updated 5 years ago
• BorjaBalle / analytic-gaussian-mechanism
  Analytic calibration for differential privacy with Gaussian perturbations
  ☆47Updated 6 years ago
• dayu11 / Gradient-Embedding-Perturbation
  ☆27Updated 2 years ago
• ebagdasa / differential-privacy-vs-fairness
  Code for "Differential Privacy Has Disparate Impact on Model Accuracy" NeurIPS'19
  ☆34Updated 3 years ago
• gdisag / gradient_disaggregation
  ☆14Updated last year
• lhfowl / robbing_the_fed
  ☆25Updated 3 years ago
• srxzr / DPSGD
  ☆20Updated 6 years ago
• ganeshdg95 / Leveraging-Adversarial-Examples-to-Quantify-Membership-Information-Leakage
  ☆19Updated 2 years ago
• BielStela / membership_inference
  Python package to create adversarial agents for membership inference attacks againts machine learning models
  ☆47Updated 6 years ago
• MinChen00 / UnlearningLeaks
  Official implementation of "When Machine Unlearning Jeopardizes Privacy" (ACM CCS 2021)
  ☆47Updated 2 years ago
• shrezaei / MI-Attack
  ☆31Updated 8 months ago