Popular GitHub Repositories for Dp

Reinforcement Learning Tutorial with Demo: DP (Policy and Value Iteration), Monte Carlo, TD Learning (SARSA, QLearning), Function Approximation, Policy Gradient, DQN, Imitation, Meta Learning, Papers, Courses, etc..

Everything you want about DP-Based Federated Learning, including Papers and Code. (Mechanism: Laplace or Gaussian, Dataset: femnist, shakespeare, mnist, cifar-10 and fashion-mnist. )

一个基于原生 PyTorch 的大型 M-LLM（文本/音频）训练库，支持张量并行 (tp)、模型并行 (cp)、数据并行 (dp) 和流水线并行 (pp)。

Private Evolution: Generating DP Synthetic Data without Training [ICLR 2024, ICML 2024 Spotlight]

The Greek NLP toolkit for Python. Supports NER/DP/POS Tagging/Greeklish-to-Greek Transliteration. Visit the playground here: https://huggingface.co/spaces/AUEB-NLP/greek-nlp-toolkit-demo (paper presented at COLING 2025)

Reference github repository for the paper "Learning to Reduce Defocus Blur by Realistically Modeling Dual-Pixel Data". We propose a procedure to generate realistic DP data synthetically. Our synthesis approach mimics the optical image formation found on DP sensors and can be applied to virtual scenes rendered with standard computer software. Leveraging these realistic synthetic DP images, we introduce a new recurrent convolutional network (RCN) architecture that can improve defocus deblurring results and is suitable for use with single-frame and multi-frame data captured by DP sensors.

Reference github repository for the paper "Improving Single-Image Defocus Deblurring: How Dual-Pixel Images Help Through Multi-Task Learning". We propose a single-image deblurring network that incorporates the two sub-aperture views into a multitask framework. Specifically, we show that jointly learning to predict the two DP views from a single blurry input image improves the network’s ability to learn to deblur the image. Our experiments show this multi-task strategy achieves +1dB PSNR improvement over state-of-the-art defocus deblurring methods. In addition, our multi-task framework allows accurate DP-view synthesis (e.g., ~ 39dB PSNR) from the single input image. These high-quality DP views can be used for other DP-based applications, such as reflection removal. As part of this effort, we have captured a new dataset of 7,059 high-quali

[ICLR'24 Spotlight] DP-OPT: Make Large Language Model Your Privacy-Preserving Prompt Engineer

DP-HyperparamTuning offers an array of tools for fast and easy hypertuning of various hyperparameters for the DP-SGD algorithm.

"Revisiting DP-Means: Fast Scalable Algorithms via Parallelism and Delayed Cluster Creation" [Dinari and Freifeld, UAI 2022]

PyTorch distributed training comparison

End-to-end codebase for finetuning LLMs (LLaMA 2, 3, etc.) with or without DP

Differentially Private Synthetic Data Generation [DP-SDG] - Experimental Setups & Knowledge Base - WORK IN PROGRESS

A toolkit for training, fine-tuning, and visualizing language models using Streamlit. Ideal for researchers and AI enthusiasts.

Azure DP-600（Fabric 分析工程师助理）考试主题和技巧

Federated Learning LLMs using Flower ai framework with client side differential privacy

这个仓库包含我在伦敦玛丽女王大学攻读硕士学位期间完成的论文项目。

Federated Learning implementation for Data Valuation and Differential Privacy, supporting Block-chain DP FL.

DP-UTIL: A Comprehensive Utility Analysis of Differential Privacy in Machine Learning

Official implementation of "DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators" (Published at TMLR 2025)