Been Kim
Google (United States)(US)Google DeepMind (United Kingdom)(GB)
Publications by Year
Research Areas
Explainable Artificial Intelligence (XAI), Adversarial Robustness in Machine Learning, Machine Learning and Data Classification, Natural Language Processing Techniques, AI-based Problem Solving and Planning
Most-Cited Works
- → Towards A Rigorous Science of Interpretable Machine Learning(2017)3,111 cited
- → SmoothGrad: removing noise by adding noise(2017)754 cited
- → Interpretability Beyond Feature Attribution: Quantitative Testing with\n Concept Activation Vectors (TCAV)(2017)732 cited
- → Sanity Checks for Saliency Maps(2018)604 cited
- Examples are not enough, learn to criticize! Criticism for Interpretability(2016)
- → The (Un)reliability of Saliency Methods(2019)432 cited
- → A Benchmark for Interpretability Methods in Deep Neural Networks(2018)379 cited
- → Human-Centered Tools for Coping with Imperfect Algorithms During Medical Decision-Making(2019)376 cited
- → Explainable deep learning for efficient and robust pattern recognition: A survey of recent developments(2021)298 cited