bias-correction

There are 49 repositories under bias-correction topic.

  • Trusted-AI/AIF360

    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.

    Language:Python2.3k90248818

  • Nicholasli1995/EvoSkeleton

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

    Language:Python331125744

  • JuliaClimate/ClimateTools.jl

    Climate science package for Julia

    Language:Julia11554918

  • ResponsiblyAI/responsibly

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

    Language:Python906720
  • python-cmethods

    btschwertfeger/python-cmethods

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

    Language:Python4832312

  • EqualityAI/EqualityML

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

    Language:Jupyter Notebook31682

  • mlr-org/mcboost

    Multi-Calibration & Multi-Accuracy Boosting for R

    Language:R305364

  • AgroClimaticTools/CDBC

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

    Language:Python26038
  • HonestyMeter

    BetterForAll/HonestyMeter

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

    Language:JavaScript253331

  • adamlilith/enmSdmX

    Tools for Modeling Niches and Distributions of Species

    Language:R21142

  • valeria-io/bias-in-credit-models

    Examples of unfairness detection for a classification-based credit model

    Language:Jupyter Notebook19103

  • maxdreyer/Reveal2Revise

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

    Language:Python17120

  • SSQ/Coursera-Ng-Improving-Deep-Neural-Networks-Hyperparameter-tuning-Regularization-and-Optimization

    Short description for quick search

    Language:Python174018

  • rsasaki0109/imu_estimator

    attitude estimator with gyro bias correction

    Language:C++1512

  • krangelie/bias-in-german-nlg

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

    Language:Jupyter Notebook14301
  • weather_forecast_bias_correction

    ldicarlo1/weather_forecast_bias_correction

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

    Language:Jupyter Notebook13102

  • IQTLabs/daisybell

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

    Language:Python12247

  • lizanafj/ensemble-bias-correction

    Bias correction method using quantile mapping

    Language:Python9102

  • mammask/droughtR

    An R package for non-stationary meteorological drought monitoring

    Language:R9103
  • BiasAdjustCXX

    btschwertfeger/BiasAdjustCXX

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

    Language:C++71152
  • bias-mitigation

    CDEIUK/bias-mitigation

    Machine Learning Bias Mitigation

    Language:Jupyter Notebook7206

  • JMitnik/FacialDebiasing

    Debiasing: Mitigating Algorithmic Facial Bias repository

    Language:Jupyter Notebook74366

  • Wazzabeee/Bias-Mitigation-In-LLM

    Research POC on the mitigation of bias in large language models (FLAN-T5 and Bloomz) through fine-tuning.

    Language:Jupyter Notebook5200

  • ehsansaleh/code_firth

    This repository contains the main ResNet backbone experiments conducted in the ICLR 2022 spotlight paper "On the Importance of Firth Bias Reduction in Few-Shot Classification".

    Language:Python4101

  • jtonglet/Twitter-Selection-Bias

    Code accompanying the thesis project: "Understanding and Correcting Selection Bias in the Sentiments derived from Flemish Tweets".

    Language:R4100

  • saulgoodenough/pad_bias_correction

    Source code of age-level bias correction

    Language:Python3111

  • Tarela/SELMA

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

    Language:Python3253

  • alexpron/mrproc

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

    Language:Python2212

  • elmomoilanen/Bootstrap-sampling-distribution

    Use bootstrap resampling to estimate the sampling distribution of a statistic

    Language:Python2100

  • kapsner/BiasCorrector

    R package providing a shiny GUI to the functions implemented in rBiasCorrection

    Language:R2100

  • mobashgr/WeLT

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

    Language:Python2401

  • morchalabi/COMPARE-suite

    Novel ultrafast suite for high-throughput & high-content multiparameter screening as in drug discovery. It has unique modules for QC, bias correction, similarity measurement, clustering and visualization. It can process hundreds of samples with many markers in a few hours not days & circumvents bath effect. It couples with any plate reader.

    Language:R2110

  • sabagh1994/code_dcf

    This repository contains the firth bias reduction experiments on the few-shot distribution calibration method conducted in the ICLR 2022 spotlight paper "On the Importance of Firth Bias Reduction in Few-Shot Classification".

    Language:Python2100

  • shuowencs/indirect-inference-panel

    Indirect inference bias correction for nonlinear panel

    Language:R2100

  • srijansood/debias-word-embeddings

    Tackling Gender and Race bias in Word Embeddings

    Language:Jupyter Notebook2301

  • shubhangkhattar/Mask-Classification-Using-CNN-Artificial-Intelligence

    Deep Learning Convolutional Neural Network (CNN) using PyTorch and train it to recognize five different classes: (1) Person without a face mask, (2) Person with a “community” (cloth) face mask, (3) Person with a “surgical” (procedural) mask, (4) Person with a “FFP2/N95/KN95”-type mask (you do not have to distinguish between them), and (5) Person with a FFP2/N95/KN95 mask that has a valve. You do not have to consider other mask types (e.g., FFP3), face shields, full/half-face respirators, PPEs, or images that do not show a single face (e.g., groups of people).

    Language:Jupyter Notebook1101