pxzhang94 Goto Github PK

a3t

This repository contains the implementation and the evaluation of our ICML 2020 paper: Robustness to Programmable String Transformations via Augmented Abstract Training.

adf

White-box Fairness Testing through Adversarial Sampling

aequitas

Bias and Fairness Audit Toolkit

aequitas-1

Aequitas, a directed fairness testing framework machine learning models.

aif360

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.

auto_lirpa

[NeurIPS 2020]auto_LiRPA: An Automatic Linear Relaxation based Perturbation Analysis Library for Neural Networks

csmath

deep-transfer-learning

A collection of implementations of deep domain adaptation algorithms

deepface

A Lightweight Face Recognition and Facial Attribute Analysis (Age, Gender, Emotion and Race) Library for Python

deepimportance_code_release

deepxplore

DeepXplore code release

eran

ETH Robustness Analyzer for Deep Neural Networks

face-classification

Face model to classify gender and race. Trained on LFWA+ Dataset.

face.evolve.pytorch

🔥🔥High-Performance Face Recognition Library on PyTorch🔥🔥

facialphenotypes

Face Verification and Identification Test Code for Racial Phenotype Evaluation on RFW and VGGFace2

fairface

insightface

Face Analysis Project on MXNet and PyTorch

lime

Lime: Explaining the predictions of any machine learning classifier

m_testing_adversatial_sample

nlp_adversarial_examples

Implementation code for the paper "Generating Natural Language Adversarial Examples"

pxzhang94.github.io

pytorch-cyclegan-and-pix2pix

Image-to-Image Translation in PyTorch

recommenders

Best Practices on Recommendation Systems

smartconcolictest

socrates

themis

Themis™ is a software fairness tester.

tog

Real-time object detection is one of the key applications of deep neural networks (DNNs) for real-world mission-critical systems. While DNN-powered object detection systems celebrate many life-enriching opportunities, they also open doors for misuse and abuse. This project presents a suite of adversarial objectness gradient attacks, coined as TOG,

tool_ui

trojannn

Trojan Attack on Neural Network

unintended-ml-bias-analysis