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We study the problem of attributing the prediction of a deep network to its input features, a problem previously studied by several other works.
The assignment game : the core
Shapley, Lloyd S. and Shubik, Martin · 1971
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Springenberg, Jost Tobias, Dosovitskiy, Alexey, Brox, Thomas, and Riedmiller, Martin A · 2014
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Going deeper with convolutions
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Explaining and harnessing adversarial examples
Goodfellow, Ian, Shlens, Jonathon, and Szegedy, Christian · 2015
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Mahendran, Aravindh and Vedaldi, Andrea · 2015
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Binder, Alexander, Montavon, Grégoire, Bach, Sebastian, Müller, Klaus-Robert, and Samek, Wojciech · 2016
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Algorithmic transparency via quantitative input influence: Theory and experiments with learning systems
Datta, A., Sen, S., and Zick, Y · 2016
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Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs
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Molecular graph convolutions: moving beyond fingerprints
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Pasupat, Panupong and Liang, Percy · 2015
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ImageNet Large Scale Visual Recognition Challenge
Russakovsky, Olga, Deng, Jia, Su, Hao, Krause, Jonathan, Satheesh, Sanjeev, Ma, Sean, Huang, Zhiheng, Karpathy, Andrej, Khosla, Aditya, Bernstein, Michael, Berg, Alexander C., and Fei-Fei, Li · 2015
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Evaluating the visualization of what a deep neural network has learned
Samek, Wojciech, Binder, Alexander, Montavon, Grégoire, Bach, Sebastian, and Müller, Klaus-Robert · 2015
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Understanding neural networks through deep visualization
Yosinski, Jason, Clune, Jeff, Nguyen, Anh Mai, Fuchs, Thomas, and Lipson, Hod · 2015
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”why should I trust you?”: Explaining the predictions of any classifier
Ribeiro, Marco Túlio, Singh, Sameer, and Guestrin, Carlos
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Model-agnostic interpretability of machine learning
Ribeiro, Marco Túlio, Singh, Sameer, and Guestrin, Carlos
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Lundberg, Scott and Lee, Su-In · 2016
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Not just a black box: Learning important features through propagating activation differences
Shrikumar, Avanti, Greenside, Peyton, Shcherbina, Anna, and Kundaje, Anshul · 2016
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Google’s neural machine translation system: Bridging the gap between human and machine translation
Wu, Yonghui, Schuster, Mike, Chen, Zhifeng, Le, Quoc V., Norouzi, Mohammad, Macherey, Wolfgang, Krikun, Maxim, Cao, Yuan, Gao, Qin, Macherey, Klaus, Klingner, Jeff, Shah, Apurva, Johnson, Melvin, Liu, Xiaobing, Kaiser, Lukasz, Gouws, Stephan, Kato, Yoshikiyo, Kudo, Taku, Kazawa, Hideto, Stevens, Keith, Kurian, George, Patil, Nishant, Wang, Wei, Young, Cliff, Smith, Jason, Riesa, Jason, Rudnick, Alex, Vinyals, Oriol, Corrado, Greg, Hughes, Macduff, and Dean, Jeffrey · 2016
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Learning important features through propagating activation differences
Shrikumar, Avanti, Greenside, Peyton, and Kundaje, Anshul · 2017
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