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"

Climate science package for Julia

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

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

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

Multi-Calibration & Multi-Accuracy Boosting for R

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

HonestyMeter: An NLP-powered framework for evaluating objectivity and bias in media content, detecting manipulative techniques, and providing actionable feedback.

Tools for Modeling Niches and Distributions of Species

Examples of unfairness detection for a classification-based credit model

Reveal to Revise: An Explainable AI Life Cycle for Iterative Bias Correction of Deep Models. Paper presented at MICCAI 2023 conference.

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

Short description for quick search

attitude estimator with gyro bias correction

Bias correction method using quantile mapping

Master thesis: Exploring bias in German NLG (GPT-3 & GerPT-2). Applies regard classification and bias mitigation triggers.

CAVAanalytics is a comprehensive framework for climate data analysis, offering streamlined access to data, advanced processing and visualization capabilities. It is designed to support a wide range of climate research and user needs

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

An R package for non-stationary meteorological drought monitoring