Alternatives and similar repositories for MICO

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

• lxuechen / private-transformers
  A codebase that makes differentially private training of transformers easy.
  ☆176Updated 2 years ago
• microsoft / dp-transformers
  Differentially-private transformers using HuggingFace and Opacus
  ☆143Updated last year
• ftramer / Handcrafted-DP
  ☆80Updated 3 years ago
• google-deepmind / jax_privacy
  Algorithms for Privacy-Preserving Machine Learning in JAX
  ☆106Updated this week
• jagielski / auditing-dpsgd
  Code for Auditing DPSGD
  ☆37Updated 3 years ago
• awslabs / fast-differential-privacy
  Fast, memory-efficient, scalable optimization of deep learning with differential privacy
  ☆132Updated 2 months ago
• shrezaei / MI-Attack
  ☆32Updated last year
• microsoft / prv_accountant
  A fast algorithm to optimally compose privacy guarantees of differentially private (DP) mechanisms to arbitrary accuracy.
  ☆74Updated last year
• cchoquette / membership-inference
  Code for the paper: Label-Only Membership Inference Attacks
  ☆66Updated 4 years ago
• MinChen00 / UnlearningLeaks
  Official implementation of "When Machine Unlearning Jeopardizes Privacy" (ACM CCS 2021)
  ☆49Updated 3 years ago
• inspire-group / membership-inference-evaluation
  Systematic Evaluation of Membership Inference Privacy Risks of Machine Learning Models
  ☆127Updated last year
• aks2203 / poisoning-benchmark
  A unified benchmark problem for data poisoning attacks
  ☆160Updated 2 years ago
• Machine-Learning-Security-Lab / mia_prune
  Membership Inference Attacks and Defenses in Neural Network Pruning
  ☆27Updated 3 years ago
• ebagdasa / differential-privacy-vs-fairness
  Code for "Differential Privacy Has Disparate Impact on Model Accuracy" NeurIPS'19
  ☆33Updated 4 years ago
• AdrienBenamira / membership_inference_attack
  Implementation of the paper : "Membership Inference Attacks Against Machine Learning Models", Shokri et al.
  ☆59Updated 6 years ago
• ganeshdg95 / Leveraging-Adversarial-Examples-to-Quantify-Membership-Information-Leakage
  ☆19Updated 2 years ago
• google-deepmind / informed_adversary_mnist_reconstruction
  ☆18Updated 3 years ago
• DennisLiu2022 / Membership-Inference-Attacks-by-Exploiting-Loss-Trajectory
  ☆24Updated 2 years ago
• cleverhans-lab / machine-unlearning
  ☆194Updated 2 years ago
• sam-yeom / ml-privacy-csf18
  Code for the CSF 2018 paper "Privacy Risk in Machine Learning: Analyzing the Connection to Overfitting"
  ☆39Updated 6 years ago
• JonasGeiping / poisoning-gradient-matching
  Witches' Brew: Industrial Scale Data Poisoning via Gradient Matching
  ☆110Updated last year
• facebookresearch / label_dp_antipodes
  Code to reproduce experiments in "Antipodes of Label Differential Privacy PATE and ALIBI"
  ☆32Updated 3 years ago
• spring-epfl / mia
  A library for running membership inference attacks against ML models
  ☆150Updated 2 years ago
• AdityaGolatkar / SelectiveForgetting
  ☆58Updated 5 years ago
• DingfanChen / RelaxLoss
  Official implementation of "RelaxLoss: Defending Membership Inference Attacks without Losing Utility" (ICLR 2022)
  ☆48Updated 3 years ago
• facebookresearch / certified-removal
  Certified Removal from Machine Learning Models
  ☆69Updated 4 years ago
• microsoft / DPSDA
  Private Evolution: Generating DP Synthetic Data without Training [ICLR 2024, ICML 2024 Spotlight]
  ☆103Updated last month
• cleverhans-lab / unrolling-sgd
  code release for "Unrolling SGD: Understanding Factors Influencing Machine Unlearning" published at EuroS&P'22
  ☆22Updated 3 years ago
• huseyinatahaninan / Differentially-Private-Fine-tuning-of-Language-Models
  ☆75Updated 3 years ago
• jinyuan-jia / MemGuard
  ☆45Updated 5 years ago