Alternatives and similar repositories for ADADP:

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

• dayu11 / Gradient-Embedding-Perturbation
  ☆27Updated 2 years ago
• woodyx218 / Deep-Learning-with-GDP-Pytorch
  Code to accompany the paper "Deep Learning with Gaussian Differential Privacy"
  ☆33Updated 3 years ago
• srxzr / DPSGD
  ☆20Updated 5 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
• lingjuanlv / FPPDL
  code for TPDS paper "Towards Fair and Privacy-Preserving Federated Deep Models"
  ☆31Updated 2 years ago
• sam-yeom / ml-privacy-csf18
  Code for the CSF 2018 paper "Privacy Risk in Machine Learning: Analyzing the Connection to Overfitting"
  ☆38Updated 6 years ago
• JunyiZhu-AI / R-GAP
  R-GAP: Recursive Gradient Attack on Privacy [Accepted at ICLR 2021]
  ☆34Updated 2 years ago
• woodyx218 / opacus_global_clipping
  ☆14Updated last year
• dayu11 / Differentially-Private-Deep-Learning
  This repo implements several algorithms for learning with differential privacy.
  ☆106Updated 2 years ago
• gdisag / gradient_disaggregation
  ☆14Updated last year
• ebagdasa / federated_adaptation
  Salvaging Federated Learning by Local Adaptation
  ☆56Updated 8 months ago
• jeremy313 / Soteria
  Official implementation of "Provable Defense against Privacy Leakage in Federated Learning from Representation Perspective"
  ☆55Updated last year
• PengchaoHan / Adaptive_Gradient_Sparsification_FL
  Adaptive gradient sparsification for efficient federated learning: an online learning approach
  ☆18Updated 4 years ago
• kamathhrishi / PATE
  Pytorch implementation of paper Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data (https://arxiv.org/abs/16…
  ☆43Updated 3 years ago
• yzeng58 / Improving-Fairness-via-Federated-Learning
  ☆13Updated 2 years ago
• facebookresearch / label_dp_antipodes
  Code to reproduce experiments in "Antipodes of Label Differential Privacy PATE and ALIBI"
  ☆30Updated 2 years ago
• ebagdasa / differential-privacy-vs-fairness
  Code for "Differential Privacy Has Disparate Impact on Model Accuracy" NeurIPS'19
  ☆34Updated 3 years ago
• ebagdasa / pytorch-privacy
  simple Differential Privacy in PyTorch
  ☆48Updated 4 years ago
• shrezaei / MI-Attack
  ☆31Updated 6 months ago
• JialinMao / private_CNN
  ☆10Updated 2 years ago
• FumiyukiKato / FL-attacks-papers
  A list of papers using/about Federated Learning especially malicious client and attacks.
  ☆12Updated 4 years ago
• shenzebang / Federated-Learning-Pytorch
  ☆40Updated last year
• SPIN-UMass / ML-Privacy-Regulization
  ☆26Updated 6 years ago
• krishnap25 / simplicial-fl
  Simplicial-FL to manage client device heterogeneity in Federated Learning
  ☆22Updated last year
• google-research / public-data-in-dpfl
  ☆22Updated 2 years 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
• ganeshdg95 / Leveraging-Adversarial-Examples-to-Quantify-Membership-Information-Leakage
  ☆19Updated 2 years ago
• ppmlguy / DP-AGD
  Concentrated Differentially Private Gradient Descent with Adaptive per-iteration Privacy Budget
  ☆49Updated 7 years ago
• Antonious-Grigis / Shuffled-Model-of-Differential-Privacy-in-Federated-Learning
  Implementation of Shuffled Model of Differential Privacy in Federated Learning." AISTATS, 2021.
  ☆17Updated 2 years ago