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| A Benchmark for Interpretability Methods in Deep Neural Networks | Sara Hooker, Dumitru Erhan, Pieter-Jan Kindermans, Been Kim | ? | [link](https://papers.nips.cc/paper/9167-a-benchmark-for-interpretability-methods-in-deep-neural-networks) | [ROAR](a-benchmark-for-interpretability-methods-in-deep-neural-networks) |
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| Fooling Neural Network Interpretations via Adversarial Model Manipulation | Juyeon Heo, Sunghwan Joo, Taesup Moon | ? | [link](https://papers.nips.cc/paper/8558-fooling-neural-network-interpretations-via-adversarial-model-manipulation) | ToDo (FK & JS) |
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| Learning Dynamics of Attention: Human Prior for Interpretable Machine Reasoning | Wonjae Kim, Yoonho Lee | ? | [link](https://papers.nips.cc/paper/8835-learning-dynamics-of-attention-human-prior-for-interpretable-machine-reasoning) | ToDo (AA) |
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| Solving Interpretable Kernel Dimensionality Reduction | Chieh Wu, Jared Miller, Yale Chang, Mario Sznaier, Jennifer Dy | ? | [link](https://papers.nips.cc/paper/9005-solving-interpretable-kernel-dimensionality-reduction) | `#F00`ToDo |
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| Solving Interpretable Kernel Dimensionality Reduction | Chieh Wu, Jared Miller, Yale Chang, Mario Sznaier, Jennifer Dy | ? | [link](https://papers.nips.cc/paper/9005-solving-interpretable-kernel-dimensionality-reduction) | Done (Ghost) |
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| This Looks Like That: Deep Learning for Interpretable Image Recognition | Chaofan Chen, Oscar Li, Daniel Tao, Alina Barnett, Cynthia Rudin, Jonathan K. Su | ? | [link](https://papers.nips.cc/paper/9095-this-looks-like-that-deep-learning-for-interpretable-image-recognition) | [link](https://docs.google.com/document/d/17zUBN_WtTL89wc-guP1kK4mr6GfwqgX5QqLOl8MKkxs/edit?usp=sharing) |
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| CXPlain: Causal Explanations for Model Interpretation under Uncertainty | Patrick Schwab, Walter Karlen | ? | [link](https://papers.nips.cc/paper/9211-cxplain-causal-explanations-for-model-interpretation-under-uncertainty) | [link](https://docs.google.com/document/d/17zUBN_WtTL89wc-guP1kK4mr6GfwqgX5QqLOl8MKkxs/edit?usp=sharing) |
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| Towards Interpretable Reinforcement Learning Using Attention Augmented Agents | Alexander Mott, Daniel Zoran, Mike Chrzanowski, Daan Wierstra, Danilo Jimenez Rezende | ? | [link](http://papers.neurips.cc/paper/9400-towards-interpretable-reinforcement-learning-using-attention-augmented-agents) | `#F00`TODO |
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