Integrated Gradients
A gradient-based attribution method that computes each input feature's contribution by integrating gradients along the path from a baseline to the input. It satisfies axioms such as sensitivity and implementation invariance.
Timeline (last 90 days)
Integrated gradients is an attribution method that assigns importance by integrating gradients along the path from a baseline to the input.
The nine evaluated XAI methods cover gradient-based methods (Vanilla Gradient, Integrated Gradients), perturbation-based methods (LIME, KernelSHAP), and propagation-rule-based methods (LRP).
All Facts (2)
Integrated gradients is an attribution method that assigns importance by integrating gradients along the path from a baseline to the input.
50%UnverifiedThe nine evaluated XAI methods cover gradient-based methods (Vanilla Gradient, Integrated Gradients), perturbation-based methods (LIME, KernelSHAP), and propagation-rule-based methods (LRP).
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