This project aims to collect the latest "call for reviewers" links from various top CS/ML/AI conferences/journals

AI-powered web scraper for harvesting and analyzing Computing Research Association job listings.

[ICLR 2024] Official PyTorch/Diffusers implementation of "Object-aware Inversion and Reassembly for Image Editing"

Papers and resources related to the security and privacy of LLMs 🤖

Open-source code for paper "Dataset Distillation"

The Python Differential Privacy Library. Built on top of: https://github.com/google/differential-privacy

Fast, flexible and easy to use probabilistic modelling in Python.

A curated list of awesome papers on dataset distillation and related applications.

Tools and service for differentially private processing of tabular and relational data

This resource mainly counts papers related to APT attacks, including APT traceability, APT knowledge graph construction, APT malicious sample detection, and APT overview. Hope these summarized pape…

A survey of privacy problems in Large Language Models (LLMs). Contains summary of the corresponding paper along with relevant code

Code for CRATE (Coding RAte reduction TransformEr).

A beautiful, simple, clean, and responsive Jekyll theme for academics

Existing Literature about Machine Unlearning

Google's differential privacy libraries.

Qlib is an AI-oriented quantitative investment platform that aims to realize the potential, empower research, and create value using AI technologies in quantitative investment, from exploring ideas…

The core library of differential privacy algorithms powering the OpenDP Project.

Deep learning images developed from nvidia/cuda-cudnn-devel-ubuntu.

Slides, paper notes, class notes, blog posts, and research on ML 📉, statistics 📊, and AI 🤖.

ICDE'22: Frequency-based Randomization for Guaranteeing Differential Privacy in Spatial Trajectories

Sample of https://github.com/Long0x0/ZJU-nCov-Hitcarder.

Educational material to learn about Goggles and how to create your own.

CogDL: A Comprehensive Library for Graph Deep Learning (WWW 2023)

Training PyTorch models with differential privacy

Python package for simple implementations of state-of-the-art LDP frequency estimation algorithms. Contains code for our VLDB 2021 Paper.

A game theoretic approach to explain the output of any machine learning model.