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marcoancona / DeepExplain

A unified framework of perturbation and gradient-based attribution methods for Deep Neural Networks interpretability. DeepExplain also includes support for Shapley Values sampling. (ICLR 2018)
https://arxiv.org/abs/1711.06104
MIT License
725 stars 133 forks source link

3D Saliency #16

Closed jdcuevas-lbl closed 6 years ago

jdcuevas-lbl commented 6 years ago

If I wanted to generate a 3D saliency map of a 64x64x64 input with 8 channels, how could I go about doing it?

marcoancona commented 6 years ago

Not sure I understand the setting. Your model input is 64x64x64x8, correct? DeepExplain generates an attribution value for each input feature so your attribution map would have the same size of the input. Then it is up to you how to visualize such multidimensional vector.

Il giorno 23 lug 2018, alle ore 20:43, jdcuevas-lbl notifications@github.com<mailto:notifications@github.com> ha scritto:

If I wanted to generate a 3D saliency map of a 64x64x64 input with 8 channels, how could I go about doing it?

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