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With the availability of large databases and recent improvements in deep learning methodology, the performance of AI systems is reaching or even exceeding the human level on an increasing number of complex tasks.
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On pixel-wise explanations for non-linear classifier decisions by layer-wise relevance propagation
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Intelligible models for healthcare: Predicting pneumonia risk and hospital 30-day readmission
R. Caruana, Y. Lou, J. Gehrke, P. Koch, M. Sturm, and N. Elhadad · 2015
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Understanding deep image representations by inverting them
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Going deeper with convolutions
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Mastering the game of go with deep neural networks and tree search
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”What is relevant in a text document?”: An interpretable machine learning approach
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Explaining recurrent neural network predictions in sentiment analysis
L. Arras, G. Montavon, K.-R. Müller, and W. Samek · 2017
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Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
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Analyzing classifiers: Fisher vectors and deep neural networks
S. Lapuschkin, A. Binder, G. Montavon, K.-R. Müller, and W. Samek · 2016
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The layer-wise relevance propagation toolbox for artificial neural networks
S. Lapuschkin, A. Binder, G. Montavon, K.-R. Müller, and W. Samek · 2016
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The mythos of model interpretability
Z. C. Lipton · 2016
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Visualizing deep convolutional neural networks using natural pre-images
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A. Nguyen, J. Yosinski, and J. Clune · 2016
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Explaining nonlinear classification decisions with deep taylor decomposition
G. Montavon, S. Bach, A. Binder, W. Samek, and K.-R. Müller · 2017
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Methods for interpreting and understanding deep neural networks
G. Montavon, W. Samek, and K.-R. Müller · 2017
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Deepstack: Expert-level artificial intelligence in heads-up no-limit poker
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Evaluating the visualization of what a deep neural network has learned
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Quantum-chemical insights from deep tensor neural networks
K. T. Schütt, F. Arbabzadah, S. Chmiela, K. R. Müller, and A. Tkatchenko · 2017
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Interpretable human action recognition in compressed domain
V. Srinivasan, S. Lapuschkin, C. Hellge, K.-R. Müller, and W. Samek · 2017
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Visualizing deep neural network decisions: Prediction difference analysis
L. M. Zintgraf, T. S. Cohen, T. Adel, and M. Welling · 2017
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