Explaining by Removing: A Unified Framework for Model Explanation | AISC

Explaining by Removing: A Unified Framework for Model Explanation | AISC

Channel:
Canada LLMs Explained - Aggregate Intellect - AI.SCIENCE
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20,300
Published on ● Video Link: https://www.youtube.com/watch?v=9P4e2Rx-Y-I


Duration: 1:01:10
698 views
22

Speaker(s): Ian Covert
Host(s): Ali Al-Sherif

Find the recording, slides, and more info at https://ai.science/e/explaining-by-removing-a-unified-framework-for-model-explanation--ao4ZaboI76dQLPhX40Bg

Motivation / Abstract
This work highlights the common patterns in 20+ different ML explanation methods including several of the most widely used approaches (SHAP, LIME, Meaningful Perturbations, permutation tests). If there was one paper, you SHOULD read to better understand the choices and assumptions made by many current explanatory methods, it is this one.

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#machinelearning #deeplearning #modelexplainability #explainableai #ai



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Tags:
deep learning
machinelearning
machine learning
explainability
model interpretability