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In this paper we propose a novel method that provides contrastive explanations justifying the classification of an input by a black box classifier such as a deep neural network.
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The organization of the human cerebral cortex estimated by intrinsic functional connectivity
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Denied persons list
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Multisite functional connectivity mri classification of autism: Abide results
Jared A Nielsen, Brandon A Zielinski, P Thomas Fletcher, Andrew L Alexander, Nicholas Lange, Erin D Bigler, Janet E Lainhart, and Jeffrey S Anderson · 2013
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Karen Simonyan, Andrea Vedaldi, and Andrew Zisserman · 2013
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Excluded parties list
Award Management System · 2013
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On pixel-wise explanations for non-linear classifier decisions by layer-wise relevance propagation
Sebastian Bach, Alexander Binder, Grégoire Montavon, Frederick Klauschen, Klaus-Robert Müller, and Wojciech Samek · 2015
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Sebastian Lapuschkin, Alexander Binder, Grégoire Montavon, Klaus-Robert Müller, and Wojciech Samek · 2016
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Tao Lei, Regina Barzilay, and Tommi Jaakkola · 2016
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Methods for interpreting and understanding deep neural networks
Grégoire Montavon, Wojciech Samek, and Klaus-Robert Müller · 2017
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Ali Mousavi, Gautam Dasarathy, and Richard G. Baraniuk · 2017
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Jose Oramas, Kaili Wang, and Tinne Tuytelaars · 2017
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Anh Nguyen, Jason Yosinski, and Jeff Clune · 2016
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”why should i trust you?” explaining the predictions of any classifier
Marco Ribeiro, Sameer Singh, and Carlos Guestrin · 2016
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Grad-cam: Visual explanations from deep networks via gradient-based localization
Ramprasaath R Selvaraju, Michael Cogswell, Abhishek Das, Ramakrishna Vedantam, Devi Parikh, and Dhruv Batra · 2016
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Interpretable two-level boolean rule learning for classification
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Nicholas Carlini and David Wagner · 2017
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Evaluating the visualization of what a deep neural network has learned
Wojciech Samek, Alexander Binder, Grégoire Montavon, Sebastian Lapuschkin, and Klaus-Robert Müller · 2017
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Unified framework for interpretable methods
Su-In Lee Scott Lundberg · 2017
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Autism classification using brain functional connectivity dynamics and machine learning
Ravi Tejwani, Adam Liska, Hongyuan You, Jenna Reinen, and Payel Das · 2017
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Ead: Elastic-net attacks to deep neural networks via adversarial examples
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Anchors: High-precision model-agnostic explanations
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Interpreting neural network judgments via minimal, stable, and symbolic corrections
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