Alternatives and similar repositories for private-evolution-papers:

Users that are interested in private-evolution-papers are comparing it to the libraries listed below

• litian96 / AdaDPS
  Private Adaptive Optimization with Side Information (ICML '22)
  ☆16Updated 2 years ago
• cleverhans-lab / unrolling-sgd
  code release for "Unrolling SGD: Understanding Factors Influencing Machine Unlearning" published at EuroS&P'22
  ☆22Updated 2 years ago
• dayu11 / Gradient-Embedding-Perturbation
  ☆27Updated 2 years ago
• lhfowl / robbing_the_fed
  ☆23Updated 3 years ago
• JunyiZhu-AI / R-GAP
  R-GAP: Recursive Gradient Attack on Privacy [Accepted at ICLR 2021]
  ☆34Updated 2 years ago
• Machine-Learning-Security-Lab / mia_prune
  Membership Inference Attacks and Defenses in Neural Network Pruning
  ☆28Updated 2 years ago
• meghdadk / SCRUB
  ☆43Updated 6 months ago
• JialinMao / private_CNN
  ☆10Updated 2 years ago
• FengHZ / BAFFLE
  The official implement of paper "Does Federated Learning Really Need Backpropagation?"
  ☆23Updated 2 years ago
• eth-sri / bayes-framework-leakage
  ☆10Updated 2 years ago
• DennisLiu2022 / Membership-Inference-Attacks-by-Exploiting-Loss-Trajectory
  ☆24Updated 2 years ago
• ganeshdg95 / Leveraging-Adversarial-Examples-to-Quantify-Membership-Information-Leakage
  ☆20Updated last year
• OPTML-Group / Unlearn-Sparse
  [NeurIPS23 (Spotlight)] "Model Sparsity Can Simplify Machine Unlearning" by Jinghan Jia*, Jiancheng Liu*, Parikshit Ram, Yuguang Yao, Gao…
  ☆66Updated 11 months ago
• google-research / public-data-in-dpfl
  ☆22Updated 2 years ago
• shash42 / Evaluating-Inexact-Unlearning
  ☆11Updated last year
• illidanlab / SplitMix
  [ICLR2022] Efficient Split-Mix federated learning for in-situ model customization during both training and testing time
  ☆41Updated last year
• justincui03 / dc_benchmark
  ☆84Updated 2 years ago
• DingfanChen / RelaxLoss
  Official implementation of "RelaxLoss: Defending Membership Inference Attacks without Losing Utility" (ICLR 2022)
  ☆48Updated 2 years ago
• jinhaoduan / SecMI
  [ICML 2023] Are Diffusion Models Vulnerable to Membership Inference Attacks?
  ☆32Updated 5 months ago
• facebookresearch / certified-removal
  Certified Removal from Machine Learning Models
  ☆64Updated 3 years ago
• AdityaGolatkar / SelectiveForgetting
  ☆56Updated 4 years ago
• Princeton-SysML / FILM
  Official repo for the paper: Recovering Private Text in Federated Learning of Language Models (in NeurIPS 2022)
  ☆57Updated last year
• facebookresearch / FL_partial_personalization
  Federated Learning with Partial Model Personalization
  ☆42Updated 2 years ago
• LINs-lab / FedTHE
  [ICLR 2023] Test-time Robust Personalization for Federated Learning
  ☆54Updated last year
• inspire-group / hydra
  Code and checkpoints of compressed networks for the paper titled "HYDRA: Pruning Adversarially Robust Neural Networks" (NeurIPS 2020) (ht…
  ☆89Updated 2 years ago
• AI-secure / CoPur
  CoPur: Certifiably Robust Collaborative Inference via Feature Purification (NeurIPS 2022)
  ☆10Updated 2 years ago
• teobaluta / etio
  Causal Reasoning for Membership Inference Attacks
  ☆10Updated 2 years ago
• AI-secure / Robustness-Against-Backdoor-Attacks
  RAB: Provable Robustness Against Backdoor Attacks
  ☆39Updated last year
• mkhodak / FedEx
  ☆12Updated 3 years ago
• ZFancy / SFAT
  [ICLR 2023] "Combating Exacerbated Heterogeneity for Robust Models in Federated Learning"
  ☆30Updated last year