1. Deep inside convolutional networks: Visualising image classification models and saliency maps;simonyan;2nd International Conference on Learning Representations ICLR 2014 - Workshop Track Proceedings,2014
2. Evaluating and Aggregating Feature-based Model Explanations
3. Towards better understanding of gradient-based attribution methods for deep neural networks;ancona;6th International Conference on Learning Representations ICLR 2018 - Conference Track Proceedings,2018
4. Towards Trustable Explainable AI
5. Learning important features through propagating activation differences;shrikumar;34th Int Conf Mach Learn ICML 2017,2017