Alternatives and similar repositories for ConTPL:

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

• yangcao888 / TPL
  Quantifying Differential Privacy under Temporal Correlations
  ☆12Updated last year
• git-disl / CLDP
  Secure and utility-aware data collection with condensed local differential privacy
  ☆17Updated 4 years ago
• vvv214 / LDP_Protocols
  Sample LDP implementation in Python
  ☆124Updated last year
• sisaman / LDP-mechanisms
  PyTorch implementation of a number of mechanisms in local differential privacy
  ☆16Updated 3 years ago
• dp-cont / dp-cont
  ☆14Updated 3 weeks ago
• git-disl / AdaTrace
  Utility-aware synthesis of differentially private and attack-resilient location traces
  ☆24Updated 6 years ago
• Samuel-Maddock / pure-LDP
  Python package for simple implementations of state-of-the-art LDP frequency estimation algorithms. Contains code for our VLDB 2021 Paper.
  ☆74Updated last year
• fricklerhandwerk / differential-privacy
  Accompanying source code to my Bachelor's thesis at TUHH
  ☆11Updated 6 years ago
• Billy1900 / Awesome-Differential-Privacy
  Differential private machine learning
  ☆190Updated 3 years ago
• imcjp / DPTrajExperiments
  本项目实现自《差分隐私下满足一致性的轨迹流量发布方法》，作者蔡剑平
  ☆12Updated 5 years ago
• ppmlguy / DP-AGD
  Concentrated Differentially Private Gradient Descent with Adaptive per-iteration Privacy Budget
  ☆49Updated 7 years ago
• hharcolezi / multi-freq-ldpy
  Multiple Frequency Estimation Under Local Differential Privacy in Python
  ☆47Updated last year
• Jun-Zhang-32108 / GFIM_LDP
  GFIM: An novel algorithm of frequent item mining with local differential privacy
  ☆12Updated 5 years ago
• forestneo / sunPytools
  Useful tools for differential privacy
  ☆215Updated 2 years ago
• zitengsun / hadamard_response
  Hadamard Response: Communication efficient, sample optimal, linear time locally private learning of distributions
  ☆14Updated 4 years ago
• BorjaBalle / amplification-by-shuffling
  Implementation of calibration bounds for differential privacy in the shuffle model
  ☆23Updated 4 years ago
• hlchengzi / 2019
  关于2019和2018年的一些东西
  ☆28Updated 5 years ago
• caicre / PrivMRF
  An implementation of "Data Synthesis via Differentially Private Markov Random Fields"
  ☆13Updated 11 months ago
• gitgik / differential-privacy-federated-learning
  Curated notebooks on how to train neural networks using differential privacy and federated learning.
  ☆66Updated 4 years ago
• AlekseiTriastcyn / bayesian-differential-privacy
  Code for the paper "Bayesian Differential Privacy for Machine Learning"
  ☆22Updated 4 years ago
• haiphanNJIT / SecureSGD
  Heterogeneous Gaussian Mechanism: Preserving Differential Privacy in Deep Learning with Provable Robustness (IJCAI'19).
  ☆13Updated 3 years ago
• lingyunhao / Deep-Learning-with-Differential-Privacy
  An implementation of Deep Learning with Differential Privacy
  ☆24Updated last year
• LapisIT / differential_privacy
  QGIS differential privacy processing plugin
  ☆22Updated 8 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
• Shubha23 / Laplace-and-Exponential-mechanisms-for-privacy
  Applying Laplace and exponential mechanisms to add random noise to data for differential privacy. Plotting MSE vs. epsilon.
  ☆29Updated 4 years ago
• hharcolezi / ldp-protocols-mobility-cdrs
  Implementation of local differential privacy mechanisms in Python language.
  ☆28Updated 2 years ago
• LDPGraphStatistics / LDPGraphStatistics
  ☆19Updated last year
• woodyx218 / Deep-Learning-with-GDP-Tensorflow
  Code to accompany the paper "Deep Learning with Gaussian Differential Privacy"
  ☆49Updated 3 years ago
• aleph-research / diff-priv-laplace-python
  Python implementation of differential privacy using Laplace mechanism
  ☆11Updated 2 years ago