The repository contains software library for Data Augmentation Services
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Updated
Aug 1, 2018 - Python
The repository contains software library for Data Augmentation Services
A method to preprocess the training data, producing an adjusted dataset that is independent of the group variable with minimum information loss.
Tensorflow implementation of Learning Not to Learn (CVPR 2019)
NeurIPS 2019 Paper: RUBi : Reducing Unimodal Biases for Visual Question Answering
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".
[ICML 2022] Channel Importance Matters in Few-shot Image Classification
Toolkit for Auditing and Mitigating Bias and Fairness of Machine Learning Systems 🔎🤖🧰
WEFE: The Word Embeddings Fairness Evaluation Framework. WEFE is a framework that standardizes the bias measurement and mitigation in Word Embeddings models. Please feel welcome to open an issue in case you have any questions or a pull request if you want to contribute to the project!
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.
Pytorch implementation of 'Explaining text classifiers with counterfactual representations' (Lemberger & Saillenfest, 2024)
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