1. Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2. Chirag Agarwal and Anh Nguyen . 2020. Explaining Image Classifiers by Removing Input Features Using Generative Models . In Computer Vision - ACCV 2020 - 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30 - December 4, 2020 , Revised Selected Papers, Part VI(Lecture Notes in Computer Science, Vol. 12627), Hiroshi Ishikawa, Cheng-Lin Liu, Tomás Pajdla, and Jianbo Shi (Eds.). Springer , 101–118. https://doi.org/10.1007/978-3-030-69544-6_7 10.1007/978-3-030-69544-6_7 Chirag Agarwal and Anh Nguyen. 2020. Explaining Image Classifiers by Removing Input Features Using Generative Models. In Computer Vision - ACCV 2020 - 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30 - December 4, 2020, Revised Selected Papers, Part VI(Lecture Notes in Computer Science, Vol. 12627), Hiroshi Ishikawa, Cheng-Lin Liu, Tomás Pajdla, and Jianbo Shi (Eds.). Springer, 101–118. https://doi.org/10.1007/978-3-030-69544-6_7
3. David Alvarez-Melis and Tommi S. Jaakkola . 2018 . Towards Robust Interpretability with Self-Explaining Neural Networks. In Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018 , NeurIPS 2018, December 3-8, 2018, Montréal, Canada, Samy Bengio, Hanna M. Wallach, Hugo Larochelle, Kristen Grauman, Nicolò Cesa-Bianchi, and Roman Garnett (Eds.). 7786–7795. https://proceedings.neurips.cc/paper/2018/hash/3e9f0fc9b2f89e043bc6233994dfcf76-Abstract.html David Alvarez-Melis and Tommi S. Jaakkola. 2018. Towards Robust Interpretability with Self-Explaining Neural Networks. In Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, NeurIPS 2018, December 3-8, 2018, Montréal, Canada, Samy Bengio, Hanna M. Wallach, Hugo Larochelle, Kristen Grauman, Nicolò Cesa-Bianchi, and Roman Garnett (Eds.). 7786–7795. https://proceedings.neurips.cc/paper/2018/hash/3e9f0fc9b2f89e043bc6233994dfcf76-Abstract.html
4. Vijay Arya Rachel K. E. Bellamy Pin-Yu Chen Amit Dhurandhar Michael Hind Samuel C. Hoffman Stephanie Houde Q. Vera Liao Ronny Luss Aleksandra Mojsilović Sami Mourad Pablo Pedemonte Ramya Raghavendra John Richards Prasanna Sattigeri Karthikeyan Shanmugam Moninder Singh Kush R. Varshney Dennis Wei and Yunfeng Zhang. 2019. One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques. (2019). https://doi.org/arXiv:1909.03012v2 arXiv:1909.03012 Vijay Arya Rachel K. E. Bellamy Pin-Yu Chen Amit Dhurandhar Michael Hind Samuel C. Hoffman Stephanie Houde Q. Vera Liao Ronny Luss Aleksandra Mojsilović Sami Mourad Pablo Pedemonte Ramya Raghavendra John Richards Prasanna Sattigeri Karthikeyan Shanmugam Moninder Singh Kush R. Varshney Dennis Wei and Yunfeng Zhang. 2019. One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques. (2019). https://doi.org/arXiv:1909.03012v2 arXiv:1909.03012
5. Or Biran and Courtenay V. Cotton. 2017. Explanation and Justification in Machine Learning : A Survey. Or Biran and Courtenay V. Cotton. 2017. Explanation and Justification in Machine Learning : A Survey.