Pre or Post-Softmax Scores in Gradient-based Attribution Methods, What is Best?

Miguel Lerma; Mirtha Lucas

doi:10.1109/icprs58416.2023.10179032

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arXiv · 2306.13197

Pre or Post-Softmax Scores in Gradient-based Attribution Methods, What is Best?

Miguel Lerma·Mirtha Lucas

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Abstract

Gradient based attribution methods for neural networks working as classifiers use gradients of network scores. Here we discuss the practical differences between using gradients of pre-softmax scores versus post-softmax scores, and their respective advantages and disadvantages.

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Miguel Lerma, Mirtha Lucas. 2023-06-22. Pre or Post-Softmax Scores in Gradient-based Attribution Methods, What is Best?. https://doi.org/10.1109/icprs58416.2023.10179032

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