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.

Official project website for the CVPR 2020 paper (Oral Presentation) "Cascaded deep monocular 3D human pose estimation wth evolutionary training data"

Toolkit for Auditing and Mitigating Bias and Fairness of Machine Learning Systems 🔎🤖🧰

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Climate science package for Julia

A collection of bias correction techniques written in Python - for climate sciences.

Climate Data Bias Corrector: A tool to bias correct the Global Climate Model (GCM)/ Regional Climate Model (RCM) simulated future climatic daily projections.

Comparison of weather station and gridded climate datasets

Machine Learning Bias Mitigation

Scan your AI/ML models for problems before you put them into production.

Debiasing: Mitigating Algorithmic Facial Bias repository

Bias correction method using quantile mapping

An R package for non-stationary meteorological drought monitoring

Multi-Calibration & Multi-Accuracy Boosting for R

Examples of unfairness detection for a classification-based credit model

A simple bias correction of temperature, dew point, and 10m wind speeds for the GFS, HRRR, and ECMWF models for two US locations.

Tools for Modeling Niches and Distributions of Species

Intrinsic bias estimation for improved analysis of bulk and single-cell chromatin accessibility profiles using SELMA

Magnetic Resonance Imaging data processing pipelines with a strong emphasis on the diffusion weighted MRI (DWI) modality and tractogram estimation

Evidence-based tools and community collaboration to end algorithmic bias, one data scientist at a time.