Code for "Revisiting Locally Differentially Private Protocols: Towards Better Trade-offs in Privacy, Utility, and Attack Resistance"

data poisoning attacks on LDP

pyDVL is a library of stable implementations of algorithms for data valuation and influence function computation

ANJANA is a Python library for anonymizing sensitive data

A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.

A Python package to assess and improve fairness of machine learning models.

Generate Diverse Counterfactual Explanations for any machine learning model.

Python package for measuring memorization in LLMs.

Library for Record and Attribute Inference

OpenLLaMA, a permissively licensed open source reproduction of Meta AI’s LLaMA 7B trained on the RedPajama dataset

The hub for EleutherAI's work on interpretability and learning dynamics

Source code for Document-level Membership Inference for Large Language Models - see https://arxiv.org/pdf/2310.15007

Official Repository for Dataset Inference for LLMs

"On the Privacy Risks of Algorithmic Recourse". Martin Pawelczyk, Himabindu Lakkaraju* and Seth Neel*. In International Conference on Artificial Intelligence and Statistics (AISTATS), PMLR, 2023.

Codes for our PETS 2024 paper "Revealing the True Cost of Locally Differentially Private Protocols: An Auditing Perspective "

Bias Auditing & Fair ML Toolkit

The implementation of "TabR: Unlocking the Power of Retrieval-Augmented Tabular Deep Learning"

A fairness library in PyTorch.

FFB: A Fair Fairness Benchmark for In-Processing Group Fairness Methods.

Official code for Does Label Differential Privacy Prevent Label Inference Attacks? (AISTATS 2023)

Code to reproduce experiments in "Antipodes of Label Differential Privacy PATE and ALIBI"

Python Package for Airborne RGB machine learning

Earth observation processing framework for machine learning in Python