FAMPE is a new attribution method that applies FFT-based frequency-selective perturbations integrated with model parameter exploration to produce fine-grained feature importance maps, showing gains over AttEXplore on ImageNet.
Rise: Randomized input sampling for explanation of black-box models
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Frequency-Aware Model Parameter Explorer: A new attribution method for improving explainability
FAMPE is a new attribution method that applies FFT-based frequency-selective perturbations integrated with model parameter exploration to produce fine-grained feature importance maps, showing gains over AttEXplore on ImageNet.