A collection of bias correction techniques written in Python - for climate sciences.
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Updated
May 26, 2024 - Python
A collection of bias correction techniques written in Python - for climate sciences.
Scan your AI/ML models for problems before you put them into production.
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.
Tools for Modeling Niches and Distributions of Species
Code to Bias Correct ICAR output based on Livneh data, using quantile mapping.
Experiments on biases in data & models
Use bootstrap resampling to estimate the sampling distribution of a statistic
Multi-Calibration & Multi-Accuracy Boosting for R
Bias correction command-line tool for climatic research written in C++
A cost-sensitive BERT that handles the class imbalance for the task of biomedical NER.
HonestyMeter: An NLP-powered framework for evaluating objectivity and bias in media content, detecting manipulative techniques, and providing actionable feedback.
An R package for non-stationary meteorological drought monitoring
Reveal to Revise: An Explainable AI Life Cycle for Iterative Bias Correction of Deep Models. Paper presented at MICCAI 2023 conference.
Bias correction method using quantile mapping
Climate science package for Julia
Scripts that I've used during grad school for data collection, analysis, visualization, cleaning, wrangling, etc., for classes, project reports, and manuscripts.
Toolkit for Auditing and Mitigating Bias and Fairness of Machine Learning Systems 🔎🤖🧰
Evidence-based tools and community collaboration to end algorithmic bias, one data scientist at a time.
An efficient and effective Bayesian calibration apporach for large-scale raw numerical model outputs
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