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

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

Simulates complex survey designs and applies Raking (IPF) calibration to reduce bias in demographic and market research studies.

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

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.

Bias correction command-line tool for climatic research written in C++

Perform partial verification bias correction for estimates of accuracy measures in diagnostic accuracy studies

LLMs Prefix Tunning approach for hate speech detection

Predicting student academic performance using machine learning, data analytics, and bias mitigation. The project analyzes how demographic, academic, and social factors affect grades while ensuring fairness across attributes like gender and past failures.

Use bootstrap resampling to estimate the sampling distribution of a statistic

This repository contains two methods to address bias to missing pixels in methane plume detection CNNs. Our methods are transferable to other tasks.

A cost-sensitive BERT that handles the class imbalance for the task of biomedical NER.

dailyword: discover a new word, once a day, straight from your terminal.

Official code for the paper “Sample Selection Bias in Machine Learning for Healthcare”

Tools for Modeling Niches and Distributions of Species

Multi-Calibration & Multi-Accuracy Boosting for R

An efficient and effective Bayesian calibration apporach for large-scale raw numerical model outputs

"Correcting bias in numerical weather forecasts using regression models and real-world environmental data."

Climate science package for Julia

Applying a BiC class incremental learning model on Distributed optical fiber acoustic sensing signal pattern recognition.