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Integrated Gradients (IG) and PatternAttribution (PA) are two established explainability methods for neural networks.
ImageNet: A large-scale hierarchical image database
Deng, J., Dong, W., Socher, R., Li, L.-J., Li, K., and Fei-Fei, L · 2009
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Very deep convolutional networks for large-scale image recognition
Simonyan, K. and Zisserman, A · 2014
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Deep inside convolutional networks: Visualising image classification models and saliency maps
Simonyan, K., Vedaldi, A., and Zisserman, A · 2014
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Striving for simplicity: The all convolutional net
Springenberg, J. T., Dosovitskiy, A., Brox, T., and Riedmiller, M · 2014
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Not just a black box: Learning important features through propagating activation differences
Shrikumar, A., Greenside, P., Shcherbina, A., and Kundaje, A · 2016
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Smoothgrad: removing noise by adding noise
Smilkov, D., Thorat, N., Kim, B., Viégas, F., and Wattenberg, M · 2017
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Axiomatic attribution for deep networks
Sundararajan, M., Taly, A., and Yan, Q · 2017
Cited alongside, same era.
Wang, Y · 2017
Cited alongside, same era.
Sanity checks for saliency maps
Adebayo, J., Gilmer, J., Muelly, M., Goodfellow, I., Hardt, M., and Kim, B · 2018
Cited alongside, same era.
Towards better understanding of gradient-based attribution methods for deep neural networks
Ancona, M., Ceolini, E., Öztireli, C., and Gross, M · 2018
Cited alongside, same era.
Learning how to explain neural networks: PatternNet and PatternAttribution
Kindermans, P.-J., Schütt, K. T., Alber, M., Müller, K.-R., Erhan, D., Kim, B., and Dähne, S · 2018
Cited alongside, same era.
Did the model understand the question?
Mudrakarta, P. K., Taly, A., Sundararajan, M., and Dhamdhere, K · 2018
iNNvestigate neural networks
Alber, M., Lapuschkin, S., Seegerer, P., Hägele, M., Schütt, K. T., Montavon, G., Samek, W., Müller, K.-R., Dähne, S., and Kindermans, P.-J · 2019
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Learning explainable models using attribution priors
Erion, G., Janizek, J. D., Sturmfels, P., Lundberg, S., and Lee, S.-I · 2019
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A benchmark for interpretability methods in deep neural networks
Hooker, S., Erhan, D., Kindermans, P.-J., and Kim, B · 2019
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Visualizing deep networks by optimizing with integrated gradients
Qi, Z., Khorram, S., and Li, F · 2019
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Understanding integrated gradients with smoothtaylor for deep neural network attribution
Goh, G. S., Lapuschkin, S., Weber, L., Samek, W., and Binder, A · 2020
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Cited alongside, same era.