Fit interpretable models. Explain blackbox machine learning.
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Updated
Jun 6, 2024 - C++
Fit interpretable models. Explain blackbox machine learning.
ChaiWithPy - the technical blog with a dash of tea
Bias detection and contextual evaluation tool for your AI projects
Bias evaluation of Differentially Private NLP models
A system to produce counterfactual explanations for biased recommendation results. We design, implement and evaluate efficient algorithms for computing counterfactual explanations that scale for large datasets.
Cocktail: A Comprehensive Information Retrieval Benchmark with LLM-Generated Documents Integration
A reading list and fortnightly discussion group designed to provoke discussion about ethical applications of, and processes for, data science.
A visualization tool to facilitate the comparison of user-implemented bias mitigation methods for AI models
A collection of inspiring resources related to engineering management and tech leadership
The bias of a single-precision floating-point number's exponent.
All code related to the Try Before you Bias (TBYB) tool based on the paper: Quantifying Bias in Text-to-Image Generative Models. You can access a hosted TBYB web-service (and comprae evaluations to other users) via: https://huggingface.co/spaces/JVice/try-before-you-bias
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.
Bird Point Count Simulator
Sampling Bias Due to Near-Duplicates in Learning to Rank
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