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cs.LG2024★ 4 cited
A Review of Global Sensitivity Analysis Methods and a comparative case study on Digit Classification
Zahra Sadeghi, Stan Matwin
Global sensitivity analysis (GSA) aims to detect influential input factors that lead a model to arrive at a certain decision and is a significant approach for mitigating the comput…
cs.LG2024
Causal Generative Explainers using Counterfactual Inference: A Case Study on the Morpho-MNIST Dataset
Will Taylor-Melanson, Zahra Sadeghi, Stan Matwin
In this paper, we propose leveraging causal generative learning as an interpretable tool for explaining image classifiers. Specifically, we present a generative counterfactual infe…