TRACE’s fixed-k cross-entropy mask search and COPAIR’s coarse-pair warm-start raise search-based visual attribution faithfulness and enable high single-point RePOPE repair rates.
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ExECG is a Python framework providing Wrapper, Explainer, and Visualizer stages to unify XAI methods for ECG models and improve reproducibility.
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A Good Initialization is All You Need for Faithful Visual Attribution
TRACE’s fixed-k cross-entropy mask search and COPAIR’s coarse-pair warm-start raise search-based visual attribution faithfulness and enable high single-point RePOPE repair rates.
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ExECG: An Explainable AI Framework for ECG models
ExECG is a Python framework providing Wrapper, Explainer, and Visualizer stages to unify XAI methods for ECG models and improve reproducibility.