Official code of "StyleT2I: Toward Compositional and High-Fidelity Text-to-Image Synthesis" (CVPR 2022)

Official code of "Discover the Unknown Biased Attribute of an Image Classifier" (ICCV 2021)

Introduction to trusted AI. Learn to use fairness algorithms to reduce and mitigate bias in data and models with aif360 and explain models with aix360

Demographic bias in misdiagnosis by computational pathology models - Nature Medicine

Notes, references and materials on AI Fairness that I found useful and helped me in my academic research.

Fairness in data, and machine learning algorithms is critical to building safe and responsible AI systems from the ground up by design. Both technical and business AI stakeholders are in constant pursuit of fairness to ensure they meaningfully address problems like AI bias. While accuracy is one metric for evaluating the accuracy of a machine le…

FairWell is a Responsible AI tool developed using Streamlit

Fairness Analysis in US Mortgage Lending with Machine Learning Algorithms

Here we deal with the issue of fairness in machine learning classification algorithm and we try to exploit regularization technique to attain fairness.

Sample project using IBM's AI Fairness 360 is an open source toolkit for determining, examining, and mitigating discrimination and bias in machine learning (ML) models throughout the AI application lifecycle.

A project on bias detection in transformer-based LLMs, with a weakly supervised approach.

AI fairness checker

A model card inspired by Derman & Wilmott's "Modelers' Hippocratic Oath", adapted for responsible and nuanced ML.

Deep-Learning approach for generating Fair and Accurate Input Representation for crime rate estimation in continuous protected attributes and continuous targets.

Explainability of AI models is a difficult task which is made simpler by Cortex Certifai. It evaluates AI models for robustness, fairness, and explainability, and allows users to compare different models or model versions for these qualities. Certifai can be applied to any black-box model including machine learning models, predictive models and …

A benchmark of the different word embedding techniques on fairness and bias in AI models